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Ismail, Susilo Widodo, and Konstantin Brazovskiy. "Spatial resolution and noise measurement of low-dose CT ACR phantom images." Journal of Physics: Conference Series 2945, no. 1 (January 1, 2025): 012013. https://doi.org/10.1088/1742-6596/2945/1/012013.
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Abstract Computed tomography (CT) is an instrument that is still widely used to diagnose and evaluate patient conditions from images produced by the CT scan process. CT scan images are formed from X-ray beams that penetrate the patient’s body and are captured by a detector and then displayed on a monitor screen. A fairly high dose of X-ray radiation is required to produce images with high resolution, good contrast, and low noise. However, this is contrary to the principles of ALARA, as low as reasonably achievable, and patient safety by using high-dose radiation. Various efforts to reduce the dose of X-ray radiation have been made. One of which is to use a low dose by operating the X-ray CT-scan machine at low voltage. Still, the consequence is that the resulting CT scan image has greater noise and lower spatial resolution compared to the image produced from the full radiation dose. This research measured spatial resolution by its modulation transfer function (MTF) and noise on open-source images taken at 25% dose by operating a 50-kV x-ray CT-scan machine on ACR phantom images using the IndoQCT application. The results are the noise of 25% dose images has an average of 86.71% greater and 41.96% lower spatial resolution than full-dose images. These results show that there are problems in using low-dose CT scans and open up opportunities to solve this problem by image reconstruction or image processing.
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Sathishkumar, B. S., and G. Nagarajan. "An efficient algorithm for computer tomography in low radiation images." Advances in Modelling and Analysis B 61, no. 4 (December 30, 2018): 189–97. http://dx.doi.org/10.18280/ama_b.610403.
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Woeltjen, Matthias Michael, Julius Henning Niehoff, Arwed Elias Michael, Sebastian Horstmeier, Christoph Moenninghoff, Jan Borggrefe, and Jan Robert Kroeger. "Low-Dose High-Resolution Photon-Counting CT of the Lung: Radiation Dose and Image Quality in the Clinical Routine." Diagnostics 12, no. 6 (June 11, 2022): 1441. http://dx.doi.org/10.3390/diagnostics12061441.
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This study aims to investigate the qualitative and quantitative image quality of low-dose high-resolution (LD-HR) lung CT scans acquired with the first clinical approved photon counting CT (PCCT) scanner. Furthermore, the radiation dose used by the PCCT is compared to a conventional CT scanner with an energy-integrating detector system (EID-CT). Twenty-nine patients who underwent a LD-HR chest CT scan with dual-source PCCT and had previously undergone a LD-HR chest CT with a standard EID-CT scanner were retrospectively included in this study. Images of the whole lung as well as enlarged image sections displaying a specific finding (lesion) were evaluated in terms of overall image quality, image sharpness and image noise by three senior radiologists using a 5-point Likert scale. The PCCT images were reconstructed with and without a quantum iterative reconstruction algorithm (PCCT QIR+/−). Noise and signal-to-noise (SNR) were measured and the effective radiation dose was calculated. Overall, image quality and image sharpness were rated best in PCCT (QIR+) images. A significant difference was seen particularly in image sections of PCCT (QIR+) images compared to EID-CT images (p < 0.005). Image noise of PCCT (QIR+) images was significantly lower compared to EID-CT images in image sections (p = 0.005). In contrast, noise was lowest on EID-CT images (p < 0.001). The PCCT used significantly less radiation dose compared to the EID-CT (p < 0.001). In conclusion, LD-HR PCCT scans of the lung provide better image quality while using significantly less radiation dose compared to EID-CT scans.
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Horenko, Illia, Lukáš Pospíšil, Edoardo Vecchi, Steffen Albrecht, Alexander Gerber, Beate Rehbock, Albrecht Stroh, and Susanne Gerber. "Low-Cost Probabilistic 3D Denoising with Applications for Ultra-Low-Radiation Computed Tomography." Journal of Imaging 8, no. 6 (May 31, 2022): 156. http://dx.doi.org/10.3390/jimaging8060156.
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We propose a pipeline for synthetic generation of personalized Computer Tomography (CT) images, with a radiation exposure evaluation and a lifetime attributable risk (LAR) assessment. We perform a patient-specific performance evaluation for a broad range of denoising algorithms (including the most popular deep learning denoising approaches, wavelets-based methods, methods based on Mumford–Shah denoising, etc.), focusing both on accessing the capability to reduce the patient-specific CT-induced LAR and on computational cost scalability. We introduce a parallel Probabilistic Mumford–Shah denoising model (PMS) and show that it markedly-outperforms the compared common denoising methods in denoising quality and cost scaling. In particular, we show that it allows an approximately 22-fold robust patient-specific LAR reduction for infants and a 10-fold LAR reduction for adults. Using a normal laptop, the proposed algorithm for PMS allows cheap and robust (with a multiscale structural similarity index >90%) denoising of very large 2D videos and 3D images (with over 107 voxels) that are subject to ultra-strong noise (Gaussian and non-Gaussian) for signal-to-noise ratios far below 1.0. The code is provided for open access.
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Li, Lu-Lu, Huang Wang, Jian Song, Jin Shang, Xiao-Ying Zhao, and Bin Liu. "A feasibility study of realizing low-dose abdominal CT using deep learning image reconstruction algorithm." Journal of X-Ray Science and Technology 29, no. 2 (March 11, 2021): 361–72. http://dx.doi.org/10.3233/xst-200826.
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OBJECTIVES: To explore the feasibility of achieving diagnostic images in low-dose abdominal CT using a Deep Learning Image Reconstruction (DLIR) algorithm. METHODS: Prospectively enrolled 47 patients requiring contrast-enhanced abdominal CT scans. The late-arterial phase scan was added and acquired using lower-dose mode (tube current range, 175–545 mA; 80 kVp for patients with BMI ≤24 kg/m2 and 100 kVp for patients with BMI > 24 kg/m2) and reconstructed with DLIR at medium setting (DLIR-M) and high setting (DLIR-H), ASIR-V at 0% (FBP), 40% and 80% strength. Both the quantitative measurement and qualitative analysis of the five types of reconstruction methods were compared. In addition, radiation dose and image quality between the early-arterial phase ASIR-V images using standard-dose and the late-arterial phase DLIR images using low-dose were compared. RESULTS: For the late-arterial phase, all five reconstructions had similar CT value (P > 0.05). DLIR-H, DLIR-M and ASIR-V80% images significantly reduced the image noise and improved the image contrast noise ratio, compared with the standard ASIR-V40% images (P < 0.05). ASIR-V80% images had undesirable image characteristics with obvious “waxy” artifacts, while DLIR-H images maintained high spatial resolution and had the highest subjective image quality. Compared with the early-arterial scans, the late-arterial phase scans significantly reduced the radiation dose (P < 0.05), while the DLIR-H images exhibited lower image noise and good display of the specific image details of lesions. CONCLUSIONS: DLIR algorithm improves image quality under low-dose scan condition and may be used to reduce the radiation dose without adversely affecting the image quality.
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Wu, Dan, Gang Wang, Bingyang Bian, Zhuohang Liu, and Dan Li. "Benefits of Low-Dose CT Scan of Head for Patients With Intracranial Hemorrhage." Dose-Response 19, no. 1 (January 1, 2020): 155932582090977. http://dx.doi.org/10.1177/1559325820909778.
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Objectives: For patients with intracranial hemorrhage (ICH), routine follow-up computed tomography (CT) scans are typically required to monitor the progression of intracranial pathology. Remarkable levels of radiation exposure are accumulated during repeated CT scan. However, the effects and associated risks have still remained elusive. This study presented an effective approach to quantify organ-specific radiation dose of repeated CT scans of head for patients with ICH. We also indicated whether a low-dose CT scan may reduce radiation exposure and keep the image quality highly acceptable for diagnosis. Methods: Herein, 72 patients with a history of ICH were recruited. The patients were divided into 4 groups and underwent CT scan of head with different tube current–time products (250, 200, 150, and 100 mAs). Two experienced radiologists visually rated scores of quality of images according to objective image noise, sharpness, diagnostic acceptability, and artifacts due to physiological noise on the same workstation. Organ-/tissue-specific radiation doses were analyzed using Radimetrics. Results: In conventional CT scan group, signal to noise ratio (SNR) and contrast to noise ratio (CNR) of ICH images were significantly higher than those in normal brain structures. Reducing the tube current–time product may decrease the image quality. However, the predilection sites for ICH could be clearly identified. The SNR and CNR in the predilection sites for ICH were notably higher than other areas. The brain, eye lenses, and salivary glands received the highest radiation dose. Reducing tube current–time product from 250 to 100 mA can significantly reduce the radiation dose. Discussion: We demonstrated that low-dose CT scan of head can still provide reasonable images for diagnosing ICH. The radiation dose can be reduced to ∼45% of the conventional CT scan group.
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Brendlin, Andreas S., David Plajer, Maryanna Chaika, Robin Wrazidlo, Arne Estler, Ilias Tsiflikas, Christoph P. Artzner, Saif Afat, and Malte N. Bongers. "AI Denoising Significantly Improves Image Quality in Whole-Body Low-Dose Computed Tomography Staging." Diagnostics 12, no. 1 (January 17, 2022): 225. http://dx.doi.org/10.3390/diagnostics12010225.
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(1) Background: To evaluate the effects of an AI-based denoising post-processing software solution in low-dose whole-body computer tomography (WBCT) stagings; (2) Methods: From 1 January 2019 to 1 January 2021, we retrospectively included biometrically matching melanoma patients with clinically indicated WBCT staging from two scanners. The scans were reconstructed using weighted filtered back-projection (wFBP) and Advanced Modeled Iterative Reconstruction strength 2 (ADMIRE 2) at 100% and simulated 50%, 40%, and 30% radiation doses. Each dataset was post-processed using a novel denoising software solution. Five blinded radiologists independently scored subjective image quality twice with 6 weeks between readings. Inter-rater agreement and intra-rater reliability were determined with an intraclass correlation coefficient (ICC). An adequately corrected mixed-effects analysis was used to compare objective and subjective image quality. Multiple linear regression measured the contribution of “Radiation Dose”, “Scanner”, “Mode”, “Rater”, and “Timepoint” to image quality. Consistent regions of interest (ROI) measured noise for objective image quality; (3) Results: With good–excellent inter-rater agreement and intra-rater reliability (Timepoint 1: ICC ≥ 0.82, 95% CI 0.74–0.88; Timepoint 2: ICC ≥ 0.86, 95% CI 0.80–0.91; Timepoint 1 vs. 2: ICC ≥ 0.84, 95% CI 0.78–0.90; all p ≤ 0.001), subjective image quality deteriorated significantly below 100% for wFBP and ADMIRE 2 but remained good–excellent for the post-processed images, regardless of input (p ≤ 0.002). In regression analysis, significant increases in subjective image quality were only observed for higher radiation doses (≥0.78, 95%CI 0.63–0.93; p < 0.001), as well as for the post-processed images (≥2.88, 95%CI 2.72–3.03, p < 0.001). All post-processed images had significantly lower image noise than their standard counterparts (p < 0.001), with no differences between the post-processed images themselves. (4) Conclusions: The investigated AI post-processing software solution produces diagnostic images as low as 30% of the initial radiation dose (3.13 ± 0.75 mSv), regardless of scanner type or reconstruction method. Therefore, it might help limit patient radiation exposure, especially in the setting of repeated whole-body staging examinations.
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Oakley, Paul A., and Deed E. Harrison. "Death of the ALARA Radiation Protection Principle as Used in the Medical Sector." Dose-Response 18, no. 2 (April 1, 2020): 155932582092164. http://dx.doi.org/10.1177/1559325820921641.
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ALARA is the acronym for “As Low As Reasonably Achievable.” It is a radiation protection concept borne from the linear no-threshold (LNT) hypothesis. There are no valid data today supporting the use of LNT in the low-dose range, so dose as a surrogate for risk in radiological imaging is not appropriate, and therefore, the use of the ALARA concept is obsolete. Continued use of an outdated and erroneous principle unnecessarily constrains medical professionals attempting to deliver high-quality care to patients by leading to a reluctance by doctors to order images, a resistance from patients/parents to receive images, subquality images, repeated imaging, increased radiation exposures, the stifling of low-dose radiation research and treatment, and the propagation of radiophobia and continued endorsement of ALARA by regulatory bodies. All these factors result from the fear of radiogenic cancer, many years in the future, that will not occur. It has been established that the dose threshold for leukemia is higher than previously thought. A low-dose radiation exposure from medical imaging will likely upregulate the body’s adaptive protection systems leading to the prevention of future cancers. The ALARA principle, as used as a radiation protection principle throughout medicine, is scientifically defunct and should be abandoned.
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Silin, A. Yu, I. S. Gruzdev, G. V. Berkovich, A. E. Nikolaev, and S. P. Morozov. "Possibilities of applying model-based iterative reconstructions in computed tomography of the lungs." Medical Visualization 24, no. 3 (October 10, 2020): 107–13. http://dx.doi.org/10.24835/1607-0763-2020-3-107-113.
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Aim: A literature review of the possibilities of applying model iterative reconstruction (MIR) in computed tomography to improve image quality, including in low-dose scanning protocols.Materials and methods. The analysis of publications devoted to the application of MIR to reduce the radiation dose and improve the quality of images in CT diagnostics of lung pathology with an emphasis on the value of the achieved radiation dose was carried out.Results. The use of MIR eliminates digital noise from medical images, improving their quality. This feature can significantly reduce radiation exposure with low-dose protocols without loss of diagnostic quality. On average, application of MIR allows to reduce the radiation dose by 70% compared to a standard protocol, without increasing the noise level of CT images and maintaining the contrast-to-noise ratio. Previous studies have shown positive experience with the use of MIR in lung cancer screening programs and monitoring of cancer patients.Conclusion. The introduction of MIR in clinical practice can optimize the radiation exposure on the population without reducing the quality of CT images, however, the threshold dose to achieve a satisfactory image quality remains unexplored.
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Zhang, Xinan. "Passive millimeter wave imaging low altitude detection technology." Applied and Computational Engineering 62, no. 1 (May 20, 2024): 211–17. http://dx.doi.org/10.54254/2755-2721/62/20240429.
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Passive millimeter wave imaging refers to the passive detection of naturally occurring background millimeter waves. After receiving external millimeter wave thermal radiation signals, the passive millimeter wave detection system will form images based on temperature differences and detect targets. Passive millimeter wave imaging has the advantages of non-radiation, non-contact, perspective imaging, good concealment, small size, and low power consumption. It is widely used in safety inspections, aircraft landing, low visibility navigation, sea surface detection and other fields. Driven by high and new technology, passive millimeter wave imaging low-altitude detection technology is rapidly developing. This paper introduced the basic principle of passive millimeter wave imaging, including the characteristics of millimeter wave radiation and Black-body radiation law, as well as its comparison with ordinary optical radiation. It also described the basic model of current passive millimeter wave imaging low altitude detection technology, explored the shortcomings of this technology and pointed out further work as well.
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Ziyad, Shabana R., Radha V., and Thavavel Vaiyapuri. "Noise Removal in Lung LDCT Images by Novel Discrete Wavelet-Based Denoising With Adaptive Thresholding Technique." International Journal of E-Health and Medical Communications 12, no. 5 (September 2021): 1–15. http://dx.doi.org/10.4018/ijehmc.20210901.oa1.
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Cancer is presently one of the prominent causes of death in the world. Early cancer detection, which can improve the prognosis and survival of cancer patients, is challenging for radiologists. Low-dose computed tomography, a commonly used imaging test for screening lung cancer, has a risk of exposure of patients to ionizing radiations. Increased radiation exposure can cause lung cancer development. However, reduced radiation dose results in noisy LDCT images. Efficient preprocessing techniques with computer-aided diagnosis tools can remove noise from LDCT images. Such tools can increase the survival of lung cancer patients by an accurate delineation of the lung nodules. This study aims to develop a framework for preprocessing LDCT images. The authors propose a noise removal technique of discrete wavelet transforms with adaptive thresholding by computing the threshold with a genetic algorithm. The performance of the proposed technique is evaluated by comparing with mean, median, and Gaussian noise filters.
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Tumialán, Luis M., Justin C. Clark, Laura A. Snyder, Gary Jasmer, and Frederick F. Marciano. "Prospective Evaluation of a Low-Dose Radiation Fluoroscopy Protocol for Minimally Invasive Transforaminal Lumbar Interbody Fusion." Operative Neurosurgery 11, no. 4 (August 11, 2015): 537–44. http://dx.doi.org/10.1227/neu.0000000000000960.
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Abstract BACKGROUND Recent research on radiation exposure in minimally invasive surgery for transforaminal lumbar interbody fusion (MIS TLIF) has led to the development of a low-dose radiation fluoroscopy protocol, with resulting reductions in fluoroscopy times and radiation exposures. OBJECTIVE To prospectively evaluate a previously reported low-dose radiation fluoroscopy protocol for MIS TLIF. METHODS A prospective evaluation of the low-dose radiation fluoroscopy protocol for MIS TLIF was performed for 65 consecutive patients. Total fluoroscopy time, radiation dose, and operative times were prospectively analyzed for all enrolled patients. RESULTS Sixty-five consecutive patients (43 women; 22 men) who underwent an MIS TLIF were prospectively enrolled in this study of the low-dose fluoroscopy protocol. A total of 260 pedicle screws were placed. The mean age of the patients was 63 years (range, 46-82 years). They had a mean operative time of 178.7 minutes (range, 119-247 minutes), a mean fluoroscopic time of 10.43 seconds (range, 5-24 seconds), and a mean radiation dose of 0.295 mGy × m2 (range, 0.092-0.314 mGy × m2). CONCLUSION The combination of low-dose pulsed images and digital spot images in a low-dose protocol decreases fluoroscopy times and radiation doses in patients undergoing MIS TLIF without compromising visualization of the bony anatomy or the safety and efficiency of the procedure. The application of this low-dose protocol uncouples the otherwise linear relationship between fluoroscopy times and radiation dose. This is due primarily to the use of the digital spot technique. Equal emphasis should be placed on radiation dose and acquisition time to optimize this protocol.
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Okumura, Miwa, Takamasa Ota, Kazuhisa Kainuma, James W. Sayre, Michael McNitt-Gray, and Kazuhiro Katada. "Effect of Edge-Preserving Adaptive Image Filter on Low-Contrast Detectability in CT Systems: Application of ROC Analysis." International Journal of Biomedical Imaging 2008 (2008): 1–6. http://dx.doi.org/10.1155/2008/379486.
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Objective. For the multislice CT (MSCT) systems with a larger number of detector rows, it is essential to employ dose-reduction techniques. As reported in previous studies, edge-preserving adaptive image filters, which selectively eliminate only the noise elements that are increased when the radiation dose is reduced without affecting the sharpness of images, have been developed. In the present study, we employed receiver operating characteristic (ROC) analysis to assess the effects of the quantum denoising system (QDS), which is an edge-preserving adaptive filter that we have developed, on low-contrast resolution, and to evaluate to what degree the radiation dose can be reduced while maintaining acceptable low-contrast resolution.Materials and Methods. The low-contrast phantoms (Catphan 412) were scanned at various tube current settings, and ROC analysis was then performed for the groups of images obtained with/without the use of QDS at each tube current to determine whether or not a target could be identified. The tube current settings for which the area under the ROC curve (Az value) was approximately 0.7 were determined for both groups of images with/without the use of QDS. Then, the radiation dose reduction ratio when QDS was used was calculated by converting the determined tube current to the radiation dose.Results. The use of the QDS edge-preserving adaptive image filter allowed the radiation dose to be reduced by up to 38%.Conclusion. The QDS was found to be useful for reducing the radiation dose without affecting the low-contrast resolution in MSCT studies.
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Sykes, Leanne M., A. Uys, C. Bradfield, and Nicolaas W. Van Reede Van Oudtshoorn. "Dental images - Their use and abuse." South African Dental Journal 75, no. 10 (November 1, 2020): 584–90. http://dx.doi.org/10.17159/2519-0105/2020/v75no10a9.
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Patients' exposure to medical and dental radiographic examination has increased over the years,1 with dental X-ray procedures now accounting for almost one-third of all radiographic examinations.2 Although they only contribute 2-4% towards the collective effective dose of exposure, all efforts should be made to minimize the amount taken and to keep exposure as low as diagnostically achievable.2
When considering radiographic examinations, the potential diagnostic or therapeutic benefits to the individual or society need to be weighed up against the possible risks that the exposure may cause, taking into account the "efficacy, and benefits and risks of alternative techniques that have the same objectives but involve no or less radiation".2,3
To this end the acronym ALARA was coined to stress that all diagnostic radiographs should aim to keep doses as low as reasonably achievable without compromising the diagnosis.1 With the advent of digital imaging there has been a trade-off between image quality and reduced radiation dosage. As such the term has been altered to ALADA, as low as diagnostically acceptable, to reflect this compromise.2
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Hurry, Jennifer K., Alan J. Spurway, Elise K. Laende, Saad Rehan, Janie L. Astephen Wilson, Michael J. Dunbar, and Ron El-Hawary. "A low-dose biplanar X-ray imager has RSA level precision in total knee arthroplasty." Acta Orthopaedica 94 (November 30, 2023): 555–59. http://dx.doi.org/10.2340/17453674.2023.19669.
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Background and purpose: The low radiation biplanar X-ray imager (EOS imaging, Paris, France) scans patients in a weight-bearing position, provides calibrated images, and limits radiation, an asset for serial radiostereometric analysis (RSA) studies. RSA in vivo precision values have not been published for this type of imaging system, thus the goal of this study was to assess the precision of RSA in vivo utilizing a low radiation biplanar imager.Patients and methods: At a mean of 5 years post-surgery (range 1.4–7.5 years), 15 total knee arthroplasty (TKA) participants (mean age 67 years at the time of imaging, 12 female, 3 male) with RSA markers implanted during index surgery were scanned twice at the same visit in the EOS imager. Precision of marker-based analysis was calculated by comparing the position of the implant relative to the underlying bone between the 2 examinations.Results: The 95% limit of precision was 0.11, 0.04, and 0.15 mm along the x, y, and z axes, respectively and 0.15°, 0.20°, and 0.14° around the same axes.Conclusion: This precision study has shown an in vivo RSA precision of ≤ 0.15 mm and ≤ 0.20°, well within published uniplanar values for conventional arthroplasty RSA, with the added benefit of weight-bearing imaging, a lower radiation dose, and without the need for a reference object during the scan.
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Xing, Yu, Qi Gang Jiang, Zhu Ping Qiao, and Wen Qing Li. "Study of Relative Radiometric Normalization Based on Multitemporal ASTER Images." Advanced Materials Research 108-111 (May 2010): 190–94. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.190.
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Both the reference image and original image are respectively decomposed into low-frequency components and high-frequency components by wavelet transform. Then, count the low-frequency components of the two images by margin calculation and select the PIF points to correct while the high-frequency components remain unchanged. Finally, reconstract the high-frequency components of discorrected original image and low-frequency components of corrected to get the corrected image. The method eliminates the radiation difference resulted from different time periods and save the radiation difference caused by the change of surface features themselves in the original image. The relative radiometric correction achieves a better effect, and can improve the accuracy of remote sensing dynamic monitoring.
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Clark, Justin C., Gary Jasmer, Frederick F. Marciano, and Luis M. Tumialán. "Minimally invasive transforaminal lumbar interbody fusions and fluoroscopy: a low-dose protocol to minimize ionizing radiation." Neurosurgical Focus 35, no. 2 (August 2013): E8. http://dx.doi.org/10.3171/2013.5.focus13144.
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Object There is an increasing awareness of radiation exposure to surgeons and the lifelong implications of such exposure. One of the main criticisms of minimally invasive transforaminal lumbar interbody fusion (MIS TLIF) is the amount of ionizing radiation required to perform the procedure. The goal in this study was to develop a protocol that would minimize the fluoroscopy time and radiation exposure needed to perform an MIS TLIF without compromising visualization of the anatomy or efficiency of the procedure. Methods A retrospective review of a prospectively collected database was performed to review the development of a low-dose protocol for MIS TLIFs in which a combination of low-dose pulsed fluoroscopy and digital spot images was used. Total fluoroscopy time and radiation dose were reviewed for 50 patients who underwent single-level MIS TLIFs. Results Fifty patients underwent single-level MIS TLIFs, resulting in the placement of 200 pedicle screws and 57 interbody spacers. There were 28 women and 22 men with an average age of 58.3 years (range 32–78 years). The mean body mass index was 26.2 kg/m2 (range 17.1–37.6 kg/m2). Indications for surgery included spondylolisthesis (32 patients), degenerative disc disease with radiculopathy (12 patients), and recurrent disc herniation (6 patients). Operative levels included 7 at L3–4, 40 at L4–5, and 3 at L5–S1. The mean operative time was 177 minutes (range 139–241 minutes). The mean fluoroscopic time was 18.72 seconds (range 7–29 seconds). The mean radiation dose was 0.247 mGy*m2 (range 0.06046–0.84054 mGy*m2). No revision surgery was required for any of the patients in this series. Conclusions Altering the fluoroscopic technique to low-dose pulse images or digital spot images can dramatically decrease fluoroscopy times and radiation doses in patients undergoing MIS TLIFs, without compromising image quality, accuracy of pedicle screw placement, or efficiency of the procedure.
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Han, Young-Joo, and Ha-Jin Yu. "Self-Supervised Noise Reduction in Low-Dose Cone Beam Computed Tomography (CBCT) Using the Randomly Dropped Projection Strategy." Applied Sciences 12, no. 3 (February 7, 2022): 1714. http://dx.doi.org/10.3390/app12031714.
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Deep learning-based denoising methods have proved efficient for medical imaging. Obtaining a three-dimensional representation of a scanned object is essential, such as in the computed tomography (CT) system. A sufficient radiation dose needs to be irradiated to a scanned object to obtain a high-quality image. However, the radiation dose is insufficient in many cases due to hardware limitations or health care issues. A deep learning-based denoising method can be a solution to obtaining good images, even when the radiation dose is insufficient. However, most existing deep learning-based denoising methods require numerous paired low-dose CT (LDCT) images and normal-dose CT (NDCT) images. It is almost impossible to obtain numerous well-paired LDCT and NDCT images. Self-supervised denoising methods were proposed to train a denoising neural network on only noisy images. These methods can be applied to the projection domain in LDCT. However, applying denoising in the projection image domain is a challenging task, because the projection images for LDCT have extremely weak signals. To solve this problem, we propose a noise reduction method based on the dropped projection strategy. The proposed method works by first reconstructing the 3D image with the degraded versions of the projection images generated by Bernoulli sampling. Subsequently, the denoising neural network is trained to restore the signal dropped out by Bernoulli sampling in the projection image domain. As such, the method we propose solves the over-smoothing problem in previous methods and is able to be trained with a small amount of data. We verified the performance of our proposed method on the SPARE challenge dataset and the in-house lithium polymer dataset. The experiments on two datasets show that the proposed method outperforms the conventional denoising methods by at least 4.47 dB of PSNR value.
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Piliero, Maria Antonietta, Margherita Casiraghi, Davide Giovanni Bosetti, Simona Cima, Letizia Deantonio, Stefano Leva, Francesco Martucci, et al. "Patient-based low dose cone beam CT acquisition settings for prostate image-guided radiotherapy treatments on a Varian TrueBeam linear accelerator." British Journal of Radiology 93, no. 1115 (November 1, 2020): 20200412. http://dx.doi.org/10.1259/bjr.20200412.
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Objective: To evaluate the performance of low dose cone beam CT (CBCT) acquisition protocols for image-guided radiotherapy of prostate cancer. Methods: CBCT images of patients undergoing prostate cancer radiotherapy were acquired with the settings currently used in our department and two low dose settings at 50% and 63% lower exposure. Four experienced radiation oncologists and two radiation therapy technologists graded the images on five image quality characteristics. The scores were analysed through Visual Grading Regression, using the acquisition settings and the patient size as covariates. Results: The low dose acquisition settings have no impact on the image quality for patients with body profile length at hip level below 100 cm. Conclusions: A reduction of about 60% of the dose is feasible for patients with size below 100 cm. The visibility of low contrast features can be compromised if using the low dose acquisition settings for patients with hip size above 100 cm. Advances in knowledge: Low dose CBCT acquisition protocols for the pelvis, based on subjective evaluation of patient images.
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Filin, Ya A., M. A. Bakhtin, D. A. Beregovskii, A. Sh Shapieva, and S. V. Tyuleneva. "Modern methods of radiation imaging of the pathology of the temporomandibular joint." Russian Journal for Personalized Medicine 4, no. 4 (September 14, 2024): 355–60. http://dx.doi.org/10.18705/2782-3806-2024-4-4-355-360.
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Modern methods of radiation imaging play an important role in the diagnosis and treatment of temporomandibular joint (TMJ) pathologies. This article examines the main imaging techniques, including radiography, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (ultrasound) and cone beam computed tomography (CBCT). Radiography, including panoramic and transcranial images, remains the main method of primary assessment of TMJ bone structures, due to its accessibility and low cost. Computed tomography with subsequent reconstruction provides detailed threedimensional images of bones, which is especially useful when planning surgical interventions, but have a high radiation dose. Magnetic resonance imaging is considered the “gold standard” for imaging TMJ soft tissues, such as the articular disc and ligaments, without the use of ionizing radiation. Ultrasound, being an affordable and noninvasive method, allows you to evaluate soft tissues in real time, but its diagnostic value depends on the experience of the operator. Cone beam computed tomography (CBCT) Combines the advantages of CT and radiography, providing highresolution images with low radiation dose, making it ideal for evaluating bone structures. Current research is also aimed at integrating hybrid imaging techniques such as PETCT and PETMRI, and using artificial intelligence to automatically interpret images. The correct choice of imaging method depends on the specific clinical situation and the objectives of the study. Modern radiation imaging technologies significantly improve the accuracy of diagnosis and the effectiveness of treatment of TMJ pathologies, providing better medical care to patients.
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Chang- Gyu Kim. "Development of a Medical Phantom to Evaluate the Function of Low Dose 3D MDCT." Medico Legal Update 20, no. 1 (April 9, 2020): 2025–30. http://dx.doi.org/10.37506/mlu.v20i1.677.
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Background/Objectives: Low dose radiation-based CT imaging is a technology that dramatically improves the information on borders between similar substances but with difference in density. The findings will serve as basic data in developing a CT phantom dedicated for X-ray phase differential imaging.Method/Statistical Analysis: To evaluate the benefits of a phantom for low dose 3D MDCT, SOMATOM Definition AS? (Siemens, Germany) CT scanner that produces 128 slices of images with one rotation was used. The auto-exposure condition (AEC) was applied as it is frequently used in clinical settings for high dose CT. After the image was acquired, a qualitative analysis was conducted to verify the practical use in a clinical setting.Findings: In order to evaluate the images acquired from the in-house produced medical phantom and the resolution in the image space, the phantom must be made of substances that have a similar actual atomic number as water. It is practical to produce the phantom for 3D CT by mixing a pure liquid and powder. The absorption, dispersion and phase differential images acquired through the low dose X-ray device were analyzed on a 5 point Likert scale. The absorption image scored 4.3 points for liquid form and 3.50 points for powder form. Both the dispersion image and the phase differential image scored 3.00 points for the liquid form and 4.50 points for the powder form, indicating that the liquid form produces better quality images in the absorption image, while the powder form produces better images in dispersion or phase differential images. The differences were statistically significant (p<0.05).Improvements/Applications: The findings show that for dispersion and phase differential images, compared to the absorption images, substances in powder form rather than liquid form are conducive to better images. These findings are expected to be of use in the field of medical imaging to produce images with high diagnostic value using low dose radiation.
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Klokov, Dmitry, and Roopa Suppiah. "AN ImageJ-BASED ALGORITHM FOR A SEMI-AUTOMATED METHOD FOR MICROSCOPIC IMAGE ENHANCEMENT AND DNA REPAIR FOCI COUNTING." AECL Nuclear Review 4, no. 1 (June 1, 2015): 75–82. http://dx.doi.org/10.12943/anr.2015.00042.
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Proper evaluation of the health risks of low-dose ionizing radiation exposure heavily relies on the ability to accurately measure very low levels of DNA damage in cells. One of the most sensitive methods for measuring DNA damage levels is the quantification of DNA repair foci that consist of macromolecular aggregates of DNA repair proteins, such as γH2AX and 53BP1, forming around individual DNA double-strand breaks. They can be quantified using immunofluorescence microscopy and are widely used as markers of DNA double-strand breaks. However this quantification, if performed manually, may be very tedious and prone to inter-individual bias. Low-dose radiation studies are especially sensitive to this potential bias due to a very low magnitude of the effects anticipated. Therefore, we designed and validated an algorithm for the semi-automated processing of microscopic images and quantification of DNA repair foci. The algorithm uses ImageJ, a freely available image analysis software that is customizable to individual cellular properties or experimental conditions. We validated the algorithm using immunolabeled 53BP1 and γH2AX in normal human fibroblast AG01522 cells under both normal and irradiated conditions. This method is easy to learn, can be used by nontrained personnel, and can help avoiding discrepancies in inter-laboratory comparison studies examining the effects of low-dose radiation.
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Epure, Cristiana, Viorel Tiganescu, Teodora Zecheru, Gabriel Epure, ovidiu Iorga, Andrei Schiopu, Mihail Munteanu, et al. "Organic Coatings with Low IR Emission." Materiale Plastice 58, no. 3 (October 5, 2021): 41–50. http://dx.doi.org/10.37358/mp.21.3.5502.
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A series of methods were employed to assess the performances of advanced coating materials based on components that can modify the spectral parameters of the surfaces on which these materials are applied in order to obtain passive military camouflage. Powder materials with high infrared (IR) reflectance were used to obtain this type of coatings, which also ingrain in their structure a significant volume of air that allow limitation of the radiative heat transfer of the coated source. The components were embedded in a polyurethane matrix, which facilitated the coating process on different surfaces. The bicomponent polyurethane-based binder used within the different composition tested is transparent to incident IR radiation, has no organic solvents, is highly flexible and possesses remarkable physical, chemical and mechanical properties: high surface adhesion, high flexibility and resistance against a number of chemical agents and external factors with destructive effect. The efficiency of these composite materials was further demonstrated by analyzing the thermal images of different objects.
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Epure, Cristiana, Viorel Tiganescu, Teodora Zecheru, Gabriel Epure, ovidiu Iorga, Andrei Schiopu, Mihail Munteanu, et al. "Organic Coatings with Low IR Emission." Materiale Plastice 58, no. 3 (October 5, 2021): 41–50. http://dx.doi.org/10.37358/mp.21.3.5502.
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A series of methods were employed to assess the performances of advanced coating materials based on components that can modify the spectral parameters of the surfaces on which these materials are applied in order to obtain passive military camouflage. Powder materials with high infrared (IR) reflectance were used to obtain this type of coatings, which also ingrain in their structure a significant volume of air that allow limitation of the radiative heat transfer of the coated source. The components were embedded in a polyurethane matrix, which facilitated the coating process on different surfaces. The bicomponent polyurethane-based binder used within the different composition tested is transparent to incident IR radiation, has no organic solvents, is highly flexible and possesses remarkable physical, chemical and mechanical properties: high surface adhesion, high flexibility and resistance against a number of chemical agents and external factors with destructive effect. The efficiency of these composite materials was further demonstrated by analyzing the thermal images of different objects.
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Sun, Meng, Tao Liu, George Barbastathis, Yincheng Qi, and Fucai Zhang. "Low-Photon Counts Coherent Modulation Imaging via Generalized Alternating Projection Algorithm." Applied Sciences 12, no. 22 (November 11, 2022): 11436. http://dx.doi.org/10.3390/app122211436.
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Phase contrast imaging is advantageous for mitigating radiation damage to samples, such as biological specimens. For imaging at nanometer or atomic resolution, the required flux on samples increases dramatically and can easily exceed the sample damage threshold. Coherent modulation imaging (CMI) can provide quantitative absorption and phase images of samples at diffraction-limited resolution with fast convergence. When used for radiation-sensitive samples, CMI experiments need to be conducted under low illumination flux for high resolution. Here, an algorithmic framework is proposed for CMI involving generalized alternating projection and total variation constraint. A five-to-ten-fold lower photon requirement can be achieved for near-field or far-field experiment dataset. The work would make CMI more applicable to the dynamics study of radiation-sensitive samples.
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López P., Alejandra, Ángela Castillo M., and Valeria Buttinghausen G. "Tomosíntesis digital mamaria: puesta al día." Revista Hospital Clínico Universidad de Chile 27, no. 1 (March 1, 2016): 46–54. http://dx.doi.org/10.5354/2735-7996.2016.71116.
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Conventional mammography has been used for decades for breast cancer screening. Its limitations are well known and are partly related to the fact that with conventional imaging, the three-dimensional volume of the breast is imaged and presented in a two-dimensional format, which leads to low sensitivity in detecting some cancers and high false-positive recall rates. Digital breast tomosynthesis consists in the acquisition of several low dose images from slightly different angles which are then sent to a computer that uses the data to generate 3-D images, providing breast images which are virtually free from superimposition. This is in particular important in cases of high mammographic density to differentiate real masses and architectural distortions from the overlying parenchyma. Digital breast tomosynthesis has shown decreased false-positive callback rates and increased rates of cancer detection, resulting in increased sensitivity and specificity, without a significant increase in the radiation dose.
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Chang- Gyu Kim. "Development of a Phantom for Low Dose Mammography." Medico Legal Update 20, no. 1 (April 9, 2020): 1887–92. http://dx.doi.org/10.37506/mlu.v20i1.653.
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Background/Objectives: Interest in regular mammography has grown as a way for early detection of breast cancer. In this study, we produced a phantom that allows for an evaluation of the image quality of images acquired at different phases using X-rays.Method/Statistical Analysis: To measure the radiation generated during breast cancer diagnosis using X-rays, the X-ray tube system by Varian was used to measure and analyze at a distance of 40 cm under the conditions of 22kVp, 20 mA, and 710mAs. To reduce errors in measurement, imaging of the breasts was done repeatedly for 10 times.Findings: In the absorption image, there were 5.0±0.2 fibers, 4.5 specks and 4.5 masses, making the total 14 which is higher than the 10 required to be officially authorized. In the dispersion and phase differential images, there were 5.5±0.0 fibers, 4.5 specks, and 4.5 masses, making the total 14.5 which is higher than the 10 required to be officially authorized. In addition the image quality was better than that of the absorption image. When a dosimeter was used, the radiation exposure was an average of 2425.85±0.33mR. When the absorbed radiation was measured using a glass dosimeter, it was 1,334±1.82?Gy. This was different from the value converted using the valid radiation.Improvements/Applications: In particular, phase differential imaging is expected to be applied to breast cancer tests where most of the tissue is soft, verification tests for foreign objects and forecasting of the progress in the disease.
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Diwakar, Manoj, Prabhishek Singh, Girija Rani Karetla, Preeti Narooka, Arvind Yadav, Rajesh Kumar Maurya, Reena Gupta, et al. "Low-Dose COVID-19 CT Image Denoising Using Batch Normalization and Convolution Neural Network." Electronics 11, no. 20 (October 19, 2022): 3375. http://dx.doi.org/10.3390/electronics11203375.
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Computed tomography (CT) is used in medical applications to produce digital medical imaging of the human body and is acquired by the reconstruction process, where X-rays are the key component of CT imaging. The present coronavirus outbreak has spawned new medical device and technology research fields. COVID-19 most severely affects people with poor immunity; children and pregnant women are more susceptible. A CT scan will be required to assess the infection’s severity. As a result, to reduce the radiation levels significantly there is a need to minimize the CT scan noise. The quality of CT images may degrade in the form of noisy images due to low radiation levels. Hence, this study proposes a novel denoising methodology for COVID-19 CT images with a low dose, where a convolution neural network (CNN) and batch normalization were utilized for denoising. From different output metrics such as peak signal-to-noise ratio (PSNR) and image quality index (IQI), the accuracy of the resulting CT images was checked and evaluated, where IQI obtained the best results in terms of 99% accuracy. The findings were also compared with the outcomes of related recent research in the domain. After a detailed review of the findings, it was noted that the proposed algorithm in the present study performed better in comparision to the existing literature.
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Li, Deng Wang, Hong Jun Wang, Da Chen, and Yong Yin. "Automated Liver Segmentation for Cone Beam CT Dataset by Probabilistic Atlas Construction." Applied Mechanics and Materials 195-196 (August 2012): 583–88. http://dx.doi.org/10.4028/www.scientific.net/amm.195-196.583.
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Cone beam CT based image guided radiation therapy can be used to measure and correct positional errors for target and critical structures immediately prior to or during the treatment delivery. Data correlation between Planning CT images and daily CBCT images is the key issue for adaptive radiation therapy, including image registration and segmentation processing. In this paper, aiming for getting accurate liver contour structures automatically in daily CBCT images which is very low-contrast comparing the planning CT, probabilistic atlas is constructed from 50 high contrast planning CT images with manual delineation by oncologist. The incoming CBCT images are registered with the atlas using the deformable registration algorithm, and the liver contour structures are generated automatically by using the deformation map. The experiment results demonstrate the efficiency of our algorithm.
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Gautam, Mahesh, Aziz Ullah, and Manish Raj Pathak. "Low Dose Computed Tomography in Diagnosis of Ureteric Calculus in Obese Patients." Journal of Nobel Medical College 9, no. 1 (June 15, 2020): 27–31. http://dx.doi.org/10.3126/jonmc.v9i1.29464.
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Background: Standard dose computed tomography is standard imaging modality in diagnosis of urolithiasis. The introduction of low dose techniques results in decrease radiation dose without significant change in image quality. However, the image quality of low dose computed tomography is affected by skin fold thickness and subcutaneous abdominal adipose tissue. The aim of this study to evaluate stone location, size, and density using low dose computed tomography compared with standard dose computed tomography in obese population.
Material and Methods: This non-randomized non-inferiority trial includes 120 patient having BMI≥25kg/m2 with acute ureteric colic. The low dose and standard dose computed tomography were performed accordingly. Effective radiation doses were calculated from dose-length product obtained from scan report using conversion factor of 0.015. The images were reconstructed using iterative reconstruction algorithm. Effective dose, number and size of stone, Hounsfield Unit value of stone and image quality was assessed.
Results: Stones were located in 69 (57.5%) in right and 51 (42.5%) in left ureter. There was no statistical difference in mean diameter, number and density of stones in low dose as compared with standard dose. The radiation dose was significantly lower with low dose. (3.68 mSv) The delineation of the ureter, outline of the stones and image quality in low dose was overall sufficient for diagnosis. No images of low dose scan were subjectively rated as non-diagnostics.
Conclusion: Low dose computed tomography with iterative reconstruction technique is as effective as standard dose in diagnosis of ureteric stones in obese patients with lower effective radiation dose.
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Spence, J. C. H., W. Qian, J. Liu, and W. Lo. "Experimental low-voltage-point projection microscopy." Proceedings, annual meeting, Electron Microscopy Society of America 51 (August 1, 1993): 1060–61. http://dx.doi.org/10.1017/s0424820100151131.
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The remarkable achievement of atomic resolution by low voltage point projection microscopy has revived interest in this instrument, and, since resolution is approximately equal to virtual source size, demonstrates field-emission from tip regions of atomic dimensions. Ray-tracing calculations show the aberration coefficients and size of the virtual source to be subnanometer. The brightness of such a nanotip has been measured to be 7.7 × 1010 A cm -2 sr -1 (at 100 kV), somewhat greater than conventional cold field emitters or synchrotrons. The images require the theory of transmission LEED for interpretation and are always out of focus by the tip to sample distance zl. Their relationship to HREM images and coherent CBED is discussed elsewhere The instruments hold promise for imaging small organic molecules (across holey carbon grids), LB and other thin organic films where radiation damage is dominated by inner-shell processes.
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Aurumskjöld, Marie-Louise, Marcus Söderberg, Fredrik Stålhammar, Kristina Vult von Steyern, Anders Tingberg, and Kristina Ydström. "Evaluation of an iterative model-based reconstruction of pediatric abdominal CT with regard to image quality and radiation dose." Acta Radiologica 59, no. 6 (August 20, 2017): 740–47. http://dx.doi.org/10.1177/0284185117728415.
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Background In pediatric patients, computed tomography (CT) is important in the medical chain of diagnosing and monitoring various diseases. Because children are more radiosensitive than adults, they require minimal radiation exposure. One way to achieve this goal is to implement new technical solutions, like iterative reconstruction. Purpose To evaluate the potential of a new, iterative, model-based method for reconstructing (IMR) pediatric abdominal CT at a low radiation dose and determine whether it maintains or improves image quality, compared to the current reconstruction method. Material and Methods Forty pediatric patients underwent abdominal CT. Twenty patients were examined with the standard dose settings and 20 patients were examined with a 32% lower radiation dose. Images from the standard examination were reconstructed with a hybrid iterative reconstruction method (iDose4), and images from the low-dose examinations were reconstructed with both iDose4 and IMR. Image quality was evaluated subjectively by three observers, according to modified EU image quality criteria, and evaluated objectively based on the noise observed in liver images. Results Visual grading characteristics analyses showed no difference in image quality between the standard dose examination reconstructed with iDose4 and the low dose examination reconstructed with IMR. IMR showed lower image noise in the liver compared to iDose4 images. Inter- and intra-observer variance was low: the intraclass coefficient was 0.66 (95% confidence interval = 0.60–0.71) for the three observers. Conclusion IMR provided image quality equivalent or superior to the standard iDose4 method for evaluating pediatric abdominal CT, even with a 32% dose reduction.
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van Sluis, Joyce, Mar Bellido, Andor W. J. M. Glaudemans, and Riemer H. J. A. Slart. "Long Axial Field-of-View PET for Ultra-Low-Dose Imaging of Non-Hodgkin Lymphoma during Pregnancy." Diagnostics 13, no. 1 (December 22, 2022): 28. http://dx.doi.org/10.3390/diagnostics13010028.
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Generally, positron emission tomography imaging is not often performed in the case of pregnant patients. The careful weighing of the risks of radiation exposure to the fetus and benefits for cancer staging and the swift onset of treatment for the mother complicates decision making in clinical practice. In oncology, the most commonly used PET radiotracer is 2-deoxy-2-[fluorine-18] fluoro-D-glucose (18F-FDG), a glucose analog which has established roles in the daily routines for, among other applications, initial diagnosis, staging, (radiation) therapy planning, and response monitoring. The introduction of long axial Field-of-View (LAFOV) PET systems allows for PET imaging with a reduced level of injected 18F-FDG activity while maintaining the image quality. Here, we discuss the first reported case of a pregnant patient diagnosed with follicular lymphoma using LAFOV PET imaging for the staging and therapy selection. The acquired PET images show diagnostic quality images with clearly distinguishable areas of lymphadenopathy, even with only 34 MBq of injected 18F-FDG activity, leading to a considerable decrease in the level of radiation exposure to the fetus.
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Kim, Hajin, Bo Kyung Cha, Kyuseok Kim, and Youngjin Lee. "Application of Adaptive Search Window-Based Nonlocal Total Variation Filter in Low-Dose Computed Tomography Images: A Phantom Study." Applied Sciences 14, no. 23 (November 24, 2024): 10886. http://dx.doi.org/10.3390/app142310886.
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Computed tomography (CT) imaging using low-dose radiation effectively reduces radiation exposure; however, it introduces noise amplification in the resulting image. This study models an adaptive nonlocal total variation (NL-TV) algorithm that efficiently reduces noise in X-ray-based images and applies it to low-dose CT images. In this study, an AAPM CT performance phantom is used, and the resulting image is obtained by applying an annotation filter and a high-pitch protocol. The adaptive NL-TV filter was designed by applying the optimal window value calculated by confirming the difference between Gaussian filtering and the basic NL-TV approach. For quantitative image quality evaluation parameters, contrast-to-noise ratio (CNR), coefficient of variation (COV), and sigma value were used to confirm the noise reduction effectiveness and spatial resolution value. The CNR and COV values in low-dose CT images using the adaptive NL-TV filter, which performed an optimization process, improved by approximately 1.29 and 1.45 times, respectively, compared with conventional NL-TV. In addition, the adaptive NL-TV filter was able to acquire spatial resolution data that were similar to a CT image without applying noise reduction. In conclusion, the proposed NL-TV filter is feasible and effective in improving the quality of low-dose CT images.
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Andellini, Martina, Francesco Faggiano, Roxana di Mauro, Pietro Derrico, and Matteo Ritrovato. "OP45 HTA Of A Pediatric Biplanar Low-Dose X-Ray Imaging System." International Journal of Technology Assessment in Health Care 34, S1 (2018): 17–18. http://dx.doi.org/10.1017/s0266462318000983.
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Introduction:Patients with adolescent idiopathic scoliosis frequently receive X-ray imaging at diagnosis and subsequent follow monitoring. To achieve the ALARA concept of radiation dose, a biplanar low-dose X-ray system (BLDS) has been proposed. The aim of the study is to gather evidence on safety, accuracy and overall effectiveness of a BLDS compared with CT scanning, in a pediatric population, in order to support the final decision on possible acquisition of such innovative diagnostic system.Methods:The new method Decision-oriented HTA (DoHTA) was applied to carefully assess the diagnostic technology. It was developed starting from the EUnetHTA Core Model® integrated with the analytic hierarchy process in order to identify all the relevant assessment aspects of the technology involved, identified from scientific literature, experts’ judgments and specific context analysis of Bambino Gesù Children's Hospital. A weight was associated to each assessment element and the alternatives’ ranking was defined.Results:This innovative system provides orthopedic images in standing or sitting position, being able to examine the spine and lower limbs under normal weight-bearing conditions. This system is recommended for particular clinical indications as scoliosis and other congenital deformities of the spine. It is able to acquire simultaneous posteroanterior and lateral images in a single scan without vertical distortion and with lower radiation exposure than CT scanning. 2D images acquired can be combined to obtain a 3D reconstruction scanning based on a semi-automated statistical model.Conclusions:The major advantages of BLDS are the relatively low dose of radiation and the possibility of obtaining a 3D reconstruction of the bones. Our preliminary results show that data on the clinical effectiveness are limited but the technical advancements of BLDS appear promising in terms of patient management and patient health outcomes associated with its use.
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Jønsson, Ásbjörn, Kjell Jonsson, Karin Eklund, Gunnila Holje, and Holger Pettersson. "Computed Radiography in Scoliosis." Acta Radiologica 36, no. 4-6 (July 1995): 429–33. http://dx.doi.org/10.1177/028418519503600419.
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The diagnostic information and radiation dose in scoliosis examinations performed with air-gap technique using stimulable phosphor imaging plates were determined in a prospective study. Overlapping p.a. images of the thoracic and lumbar spine in 9 patients were obtained with 4 different exposure settings according to patient size. Equal exposure settings were used for the 2 images. Two images of 18 were judged inferior in depicting the landmarks of scoliosis measurement, requiring re-exposure. Sixteen images were judged of adequate or good quality. The mean entrance doses in the central beam for the 4 patient groups were in the interval of 0.05 to 0.12 mGy for both images. The skin doses on the breasts were in the range of 0.00 to 0.03 mGy. The presented technique thus results in a low radiation dose with sufficient diagnostic information in radiography of scoliosis.
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Kalra, Mannudeep K., Conrad Wittram, Michael M. Maher, Amita Sharma, Gopal B. Avinash, Kelly Karau, Thomas L. Toth, Elkan Halpern, Sanjay Saini, and Jo-Anne Shepard. "Can Noise Reduction Filters Improve Low-Radiation-Dose Chest CT Images? Pilot Study." Radiology 228, no. 1 (July 2003): 257–64. http://dx.doi.org/10.1148/radiol.2281020606.
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Godt, Johannes Clemens, Cathrine K. Johansen, Anne Catrine T. Martinsen, Anselm Schulz, Helga M. Brøgger, Kristin Jensen, Arne Stray-Pedersen, and Johann Baptist Dormagen. "Iterative reconstruction improves image quality and reduces radiation dose in trauma protocols; A human cadaver study." Acta Radiologica Open 10, no. 10 (October 2021): 205846012110553. http://dx.doi.org/10.1177/20584601211055389.
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Background Radiation-related cancer risk is an object of concern in CT of trauma patients, as these represent a young population. Different radiation reducing methods, including iterative reconstruction (IR), and spilt bolus techniques have been introduced in the recent years in different large scale trauma centers. Purpose To compare image quality in human cadaver exposed to thoracoabdominal computed tomography using IR and standard filtered back-projection (FBP) at different dose levels. Material and methods Ten cadavers were scanned at full dose and a dose reduction in CTDIvol of 5 mGy (low dose 1) and 7.5 mGy (low dose 2) on a Siemens Definition Flash 128-slice computed tomography scanner. Low dose images were reconstructed with FBP and Sinogram affirmed iterative reconstruction (SAFIRE) level 2 and 4. Quantitative image quality was analyzed by comparison of contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR). Qualitative image quality was evaluated by use of visual grading regression (VGR) by four radiologists. Results Readers preferred SAFIRE reconstructed images over FBP at a dose reduction of 40% (low dose 1) and 56% (low dose 2), with significant difference in overall impression of image quality. CNR and SNR showed significant improvement for images reconstructed with SAFIRE 2 and 4 compared to FBP at both low dose levels. Conclusions Iterative image reconstruction, SAFIRE 2 and 4, resulted in equal or improved image quality at a dose reduction of up to 56% compared to full dose FBP and may be used a strong radiation reduction tool in the young trauma population.
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Gukova, A. D., V. V. Petrovskaya, and Ya A. Lubashev. "Optimization of Radiation Exposure when Examining Patients with Pathology of the Craniovertebral Region." Radiology - Practice, no. 2 (December 10, 2023): 10–26. http://dx.doi.org/10.52560/2713-0118-2024-2-10-26.
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The diagnostics are based on the principle of obtaining informative and high-quality images with minimal radiation exposure using radiation diagnostic methods: traditional radiography, multislice and cone-beam computed tomography.When conducting X-ray examinations, the main factors in reducing the risk of radiation exposure are the use of highly sensitive digital diagnostic image receivers, minimal exposure time, and a minimum number of images per examination. A lower current value and high anode voltage values, a minimum focal spot size, the placement of the tube as far as possible from the patient and the image receiver as close to the patient as possible, collimation of the radiation beam, and preference for a low radiation dose rate mode are also factors in reducing the risk of radiation exposure.Imaging of the craniovertebral region using cone beam computed tomography offers the opportunity to evaluate the bone structure of the region in detail, with an equal or less effective dose to the patient.
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Левитов, А., A. Levitov, В. Дога, V. Doga, Г. Белицкая, and G. Belitskaya. "Slot-Radiography. New Possibilities of Radiation Diagnostics." Medical Radiology and radiation safety 64, no. 1 (January 20, 2019): 74–79. http://dx.doi.org/10.12737/article_5c55fb630f2228.33688535.
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Slot-radiography is an x-ray examination in which a two-dimensional radiography with a straight beam and further computer stitching of the images obtained on the workstation during a single-pass of x-ray tube over a patient. The application of innovative techniques for image acquisition and processing in combination with a large-area flat panel detector (FPD) makes it possible to produce long-view images from one to several anatomical regions. During the investigation, the x-ray tube and the FPD move simultaneously at a constant speed in parallel relative to one another with the longitudinal axis of the body. Thus, it makes possible to obtain images with little distortion and processed images without visual defects. And this allows conducting more accurate diagnosis of pathological changes. Slot-radiography can be performed both in the patient’s standing position and lying down depending on the region of interest and tasks. It is possible to obtain images in both a frontal and a lateral projection without loss of quality.
Slot-radiography is effectively used to diagnose pathological changes in joints and spine, including scoliosis, limb shortening, segmental spinal instability, pathology of lower limb veins, and also as a method for assessing the quality of the treatment. This technique is characterized by safety and convenience for the patient: minimal time costs and low radiation exposure.
The application of this technique significantly increases the informative value of the x-ray examination, brings it to a qualitatively new level, providing a physician with a wide range of diagnostic possibilities.
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Shvaiko, Valerii, Olena Bandurka, Vadym Shpuryk, and Yevhen V. Havrylko. "METHODS FOR DETECTING FIRES IN ECOSYSTEMS USING LOW-RESOLUTION SPACE IMAGES." Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska 11, no. 1 (March 31, 2021): 15–19. http://dx.doi.org/10.35784/iapgos.2576.
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The paper presents the methods for fire identification using low-resolution space images obtained from Terra Modis and NOAA satellites. There are lots of algorithms to identify potentially "fire pixels" (PF). They are based on the assessment of temperature in spectral ranges from 3.5–4 to 10.5–11.5 microns. One of the problematic aspects in the Fire Detection Method using low-resolution space images is "Cloud and Water Masking". To identify "fire pixels", it is important to exclude from the analysis fragments of images that are covered with clouds and occupied by water objects. Identification of pixels in which one or more fires are actively burning at the time of passing over the Earth is the basis of the algorithm for detecting potentially "fire pixels". The algorithm requires a significant increase in radiation in the range of 4 micrometers, as well as on the observed radiation in the range of 11 micrometers. The algorithm investigates each pixel in a scene that is assigned one of the following classes as a result: lack of data, cloud, water, potentially fire or uncertain. The pixels that lack actual data are immediately classified as "missing data (NULL)" and excluded from further consideration. Cloud and water pixels, defined by the cloud masking technique and water objects, belong to cloud and water classes, respectively. The fire detection algorithm investigates only those pixels of the Earth's surface that are classified as potentially fire or uncertain. The method was implemented using the Visual Programming Tool PowerBuilder in the data processing system of Erdas Imaging. As a result of the use of the identification method, fires in the Chornobyl exclusion zone, steppe fires and fires at gas wells were detected. Using the method of satellite fire identification is essential for the prompt detection of fires for remote forests or steppes that are poorly controlled by ground monitoring methods.
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Monuszko, Karen, Michael Malinzak, Lexie Zidanyue Yang, Donna Niedzwiecki, Herbert Fuchs, Carrie R. Muh, Krista Gingrich, Robert Lark, and Eric M. Thompson. "Image quality of EOS low-dose radiography in comparison with conventional radiography for assessment of ventriculoperitoneal shunt integrity." Journal of Neurosurgery: Pediatrics 27, no. 4 (April 2021): 375–81. http://dx.doi.org/10.3171/2020.8.peds20428.
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OBJECTIVE Patients with shunted hydrocephalus often accumulate high levels of radiation over their lifetimes during evaluation of hardware integrity. Current practice involves the use of a series of conventional radiographs for this purpose. Newer low-dose EOS radiography is currently used to evaluate scoliosis but has not been explored to evaluate shunt integrity on a large scale. The goal of this study was to compare the quality of imaging using EOS low-dose radiography to conventional radiography to evaluate shunt tubing. METHODS A retrospective chart review was performed on 57 patients who previously had both conventional radiographs and low-dose EOS images of their cerebral shunt tubing from 2000 to 2018. Patient demographics (age, sex, type of shunt tubing, primary diagnosis) were collected. Conventional radiographic images and low-dose EOS images were independently analyzed by a neurosurgeon and neuroradiologist in three categories: image quality, delineation of shunt, and distinction of shunt compared to adjacent anatomy. RESULTS All patients had shunted hydrocephalus due to spina bifida and Chiari type II malformation. Ratings of EOS and conventional radiographic images by both raters did not differ significantly in terms of image quality (rater 1, p = 0.499; rater 2, p = 0.578) or delineation of shunt (p = 0.107 and p = 0.256). Conventional radiographic images received significantly higher ratings than EOS on the ability to distinguish the shunt versus adjacent anatomy by rater 1 (p = 0.039), but not by rater 2 (p = 0.149). The overall score of the three categories combined was not significantly different between EOS and conventional radiography (rater 1, p = 0.818; rater 2, p = 0.186). In terms of cost, an EOS image was less costly than a conventional radiography shunt series ($236–$366 and $1300–$1547, respectively). The radiation dose was also lower for EOS images, with an effective dose of 0.086–0.140 mSv compared to approximately 1.6 mSv for a similar field of view with conventional radiography. CONCLUSIONS The image quality of low-dose EOS radiography does not significantly differ from conventional radiography for the evaluation of cerebral shunts. In addition, EOS affords a much lower radiation dose and a lower cost.
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Mahmoodian, Naghmeh, Mohammad Rezapourian, Asim Abdulsamad Inamdar, Kunal Kumar, Melanie Fachet, and Christoph Hoeschen. "Enabling Low-Dose In Vivo Benchtop X-ray Fluorescence Computed Tomography through Deep-Learning-Based Denoising." Journal of Imaging 10, no. 6 (May 22, 2024): 127. http://dx.doi.org/10.3390/jimaging10060127.
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X-ray Fluorescence Computed Tomography (XFCT) is an emerging non-invasive imaging technique providing high-resolution molecular-level data. However, increased sensitivity with current benchtop X-ray sources comes at the cost of high radiation exposure. Artificial Intelligence (AI), particularly deep learning (DL), has revolutionized medical imaging by delivering high-quality images in the presence of noise. In XFCT, traditional methods rely on complex algorithms for background noise reduction, but AI holds promise in addressing high-dose concerns. We present an optimized Swin-Conv-UNet (SCUNet) model for background noise reduction in X-ray fluorescence (XRF) images at low tracer concentrations. Our method’s effectiveness is evaluated against higher-dose images, while various denoising techniques exist for X-ray and computed tomography (CT) techniques, only a few address XFCT. The DL model is trained and assessed using augmented data, focusing on background noise reduction. Image quality is measured using peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM), comparing outcomes with 100% X-ray-dose images. Results demonstrate that the proposed algorithm yields high-quality images from low-dose inputs, with maximum PSNR of 39.05 and SSIM of 0.86. The model outperforms block-matching and 3D filtering (BM3D), block-matching and 4D filtering (BM4D), non-local means (NLM), denoising convolutional neural network (DnCNN), and SCUNet in both visual inspection and quantitative analysis, particularly in high-noise scenarios. This indicates the potential of AI, specifically the SCUNet model, in significantly improving XFCT imaging by mitigating the trade-off between sensitivity and radiation exposure.
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Feng, Zhiwei, Ailong Cai, Yizhong Wang, Lei Li, Li Tong, and Bin Yan. "Dual residual convolutional neural network (DRCNN) for low-dose CT imaging." Journal of X-Ray Science and Technology 29, no. 1 (February 19, 2021): 91–109. http://dx.doi.org/10.3233/xst-200777.
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The excessive radiation doses in the application of computed tomography (CT) technology pose a threat to the health of patients. However, applying a low radiation dose in CT can result in severe artifacts and noise in the captured images, thus affecting the diagnosis. Therefore, in this study, we investigate a dual residual convolution neural network (DRCNN) for low-dose CT (LDCT) imaging, whereby the CT images are reconstructed directly from the sinogram by integrating analytical domain transformations, thus reducing the loss of projection information. With this new framework, feature extraction is performed simultaneously on both the sinogram-domain sub-net and the image-domain sub-net, which utilize the residual shortcut networks and play a complementary role in suppressing the projection noise and reducing image error. This new DRCNN approach helps not only decrease the sinogram noise but also preserve significant structural information. The experimental results of simulated and real projection data demonstrate that our DRCNN achieve superior performance over other state-of-art methods in terms of visual inspection and quantitative metrics. For example, comparing with RED-CNN and DP-ResNet, the value of PSNR using our DRCNN is improved by nearly 3 dB and 1 dB, respectively.
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Pathak, Yadunath, K. V. Arya, and Shailendra Tiwari. "Low-dose CT image reconstruction using gain intervention-based dictionary learning." Modern Physics Letters B 32, no. 14 (May 20, 2018): 1850148. http://dx.doi.org/10.1142/s0217984918501488.
Full textAbstract:
Computed tomography (CT) approach is extensively utilized in clinical diagnoses. However, X-ray residue in human body may introduce somatic damage such as cancer. Owing to radiation risk, research has focused on the radiation exposure distributed to patients through CT investigations. Therefore, low-dose CT has become a significant research area. Many researchers have proposed different low-dose CT reconstruction techniques. But, these techniques suffer from various issues such as over smoothing, artifacts, noise, etc. Therefore, in this paper, we have proposed a novel integrated low-dose CT reconstruction technique. The proposed technique utilizes global dictionary-based statistical iterative reconstruction (GDSIR) and adaptive dictionary-based statistical iterative reconstruction (ADSIR)-based reconstruction techniques. In case the dictionary (D) is predetermined, then GDSIR can be used and if D is adaptively defined then ADSIR is appropriate choice. The gain intervention-based filter is also used as a post-processing technique for removing the artifacts from low-dose CT reconstructed images. Experiments have been done by considering the proposed and other low-dose CT reconstruction techniques on well-known benchmark CT images. Extensive experiments have shown that the proposed technique outperforms the available approaches.
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Alsamadony, Khalid L., Ertugrul U. Yildirim, Guenther Glatz, Umair Bin Waheed, and Sherif M. Hanafy. "Deep Learning Driven Noise Reduction for Reduced Flux Computed Tomography." Sensors 21, no. 5 (March 9, 2021): 1921. http://dx.doi.org/10.3390/s21051921.
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Deep neural networks have received considerable attention in clinical imaging, particularly with respect to the reduction of radiation risk. Lowering the radiation dose by reducing the photon flux inevitably results in the degradation of the scanned image quality. Thus, researchers have sought to exploit deep convolutional neural networks (DCNNs) to map low-quality, low-dose images to higher-dose, higher-quality images, thereby minimizing the associated radiation hazard. Conversely, computed tomography (CT) measurements of geomaterials are not limited by the radiation dose. In contrast to the human body, however, geomaterials may be comprised of high-density constituents causing increased attenuation of the X-rays. Consequently, higher-dose images are required to obtain an acceptable scan quality. The problem of prolonged acquisition times is particularly severe for micro-CT based scanning technologies. Depending on the sample size and exposure time settings, a single scan may require several hours to complete. This is of particular concern if phenomena with an exponential temperature dependency are to be elucidated. A process may happen too fast to be adequately captured by CT scanning. To address the aforementioned issues, we apply DCNNs to improve the quality of rock CT images and reduce exposure times by more than 60%, simultaneously. We highlight current results based on micro-CT derived datasets and apply transfer learning to improve DCNN results without increasing training time. The approach is applicable to any computed tomography technology. Furthermore, we contrast the performance of the DCNN trained by minimizing different loss functions such as mean squared error and structural similarity index.
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Cardim, Guilherme P., Claudio B. Reis Neto, Eduardo S. Nascimento, Henrique P. Cardim, Wallace Casaca, Rogério G. Negri, Flávio C. Cabrera, Renivaldo J. dos Santos, Erivaldo A. da Silva, and Mauricio Araujo Dias. "A Study of COVID-19 Diagnosis Applying Artificial Intelligence to X-Rays Images." Computers 14, no. 5 (April 28, 2025): 163. https://doi.org/10.3390/computers14050163.
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X-ray imaging, as a technique of non-destructive testing, has demonstrated considerable promise in COVID-19 diagnosis, particularly if supplemented with artificial intelligence (AI). Both radiologic technologists and AI researchers have raised the alarm about having to use increased doses of radiation in order to get more refined images and, hence, enhance diagnostic precision. In this research, we assess whether the disparity in exposure to the radiation dose considerably influences the credibility of AI-based diagnostic systems for COVID-19. A heterogeneous dataset of chest X-rays acquired at varying degrees of radiation exposure was run through four convolutional neural networks: VGG16, VGG19, ResNet50, and ResNet50V2. Results indicated above 91% accuracies, demonstrating that greater radiation exposure does not appreciably enhance diagnostic accuracy. Low radiation exposure sufficient to be utilized by human radiologists is therefore adequate for AI-based diagnosis. These findings are useful to the medical community, emphasizing that maximum diagnostic accuracy using AI does not need increased doses of radiation, thus further guaranteeing the safe application of X-ray imaging in COVID-19 diagnosis and possibly other medical and veterinary applications.
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You, Yun-Wen, Hsun-Yun Chang, Hua-Yang Liao, Wei-Lun Kao, Guo-Ji Yen, Chi-Jen Chang, Meng-Hung Tsai, and Jing-Jong Shyue. "Electron Tomography of HEK293T Cells Using Scanning Electron Microscope–Based Scanning Transmission Electron Microscopy." Microscopy and Microanalysis 18, no. 5 (October 2012): 1037–42. http://dx.doi.org/10.1017/s1431927612001158.
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AbstractBased on a scanning electron microscope operated at 30 kV with a homemade specimen holder and a multiangle solid-state detector behind the sample, low-kV scanning transmission electron microscopy (STEM) is presented with subsequent electron tomography for three-dimensional (3D) volume structure. Because of the low acceleration voltage, the stronger electron-atom scattering leads to a stronger contrast in the resulting image than standard TEM, especially for light elements. Furthermore, the low-kV STEM yields less radiation damage to the specimen, hence the structure can be preserved. In this work, two-dimensional STEM images of a 1-μm-thick cell section with projection angles between ±50° were collected, and the 3D volume structure was reconstructed using the simultaneous iterative reconstructive technique algorithm with the TomoJ plugin for ImageJ, which are both public domain software. Furthermore, the cross-sectional structure was obtained with the Volume Viewer plugin in ImageJ. Although the tilting angle is constrained and limits the resulting structural resolution, slicing the reconstructed volume generated the depth profile of the thick specimen with sufficient resolution to examine cellular uptake of Au nanoparticles, and the final position of these nanoparticles inside the cell was imaged.
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Arsénio, Marta, Ricardo Vigário, and Ana M. Mota. "Recovering Image Quality in Low-Dose Pediatric Renal Scintigraphy Using Deep Learning." Journal of Imaging 11, no. 3 (March 19, 2025): 88. https://doi.org/10.3390/jimaging11030088.
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The objective of this study is to propose an advanced image enhancement strategy to address the challenge of reducing radiation doses in pediatric renal scintigraphy. Data from a public dynamic renal scintigraphy database were used. Based on noisier images, four denoising neural networks (DnCNN, UDnCNN, DUDnCNN, and AttnGAN) were evaluated. To evaluate the quality of the noise reduction, with minimal detail loss, the kidney signal-to-noise ratio (SNR) and multiscale structural similarity (MS-SSIM) were used. Although all the networks reduced noise, UDnCNN achieved the best balance between SNR and MS-SSIM, leading to the most notable improvements in image quality. In clinical practice, 100% of the acquired data are summed to produce the final image. To simulate the dose reduction, we summed only 50%, simulating a proportional decrease in radiation. The proposed deep-learning approach for image enhancement ensured that half of all the frames acquired may yield results that are comparable to those of the complete dataset, suggesting that it is feasible to reduce patients’ exposure to radiation. This study demonstrates that the neural networks evaluated can markedly improve the renal scintigraphic image quality, facilitating high-quality imaging with lower radiation doses, which will benefit the pediatric population considerably.
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CHAKRABORTY, ARINDAM, and J. SRINIVASAN. "Comparison of radiative fluxes at the top of the atmosphere from INSAT and ERBE." MAUSAM 54, no. 1 (January 18, 2022): 299–314. http://dx.doi.org/10.54302/mausam.v54i1.1514.
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An accurate knowledge of radiative fluxes at the Top of the Atmosphere (TOA) is necessary to study the variability of climate. Many geostationary satellites have been measuring radiative fluxes in a narrow spectral band in the infrared and visible regions during the past 30 years. This data will be useful for climate studies if it can be converted to total radiative fluxes. In this paper we demonstrate that the errors in monthly mean Outgoing Longwave Radiation (OLR) at the TOA obtained from the Indian geostationary satellite INSAT-1B is less than 15 W m-2 in most of the regions when compared to the data from the Earth Radiation Budget Experiment (ERBE). This indicates that the conversion of INSAT narrowband flux to broadband flux does not result in large errors. This could be on account of high water vapour content in the Indian region. The error in INSAT OLR has been shown to be dependent on number of images available per month. INSAT albedo has a negative bias over ocean when compared to ERBE on account of the isotropic reflectance assumption. No such bias was noticed over land. This low albedo bias in INSAT was removed by adding a constant term equal to 2% over ocean. It has been shown that the effect of Sun Glint in clear sky albedo can be removed if two images per day are used for the calculation of albedo. The difference in net radiation at the TOA between INSAT and ERBE has been shown to be within 10 W m-2. In some regions, such as Saudi Arabia (from December 1988 to March 1989) the difference between ERBE and INSAT estimated net radiation (~10 W m-2) was found to be less than the difference between two ERBE satellite observations (~20 W m-2). This indicates clearly that diurnal variation of net radiation can cause large errors in the estimates of monthly mean net radiation.