To see the other types of publications on this topic, follow the link: Diagnostic imaging. Algorithms.
Journal articles on the topic 'Diagnostic imaging. Algorithms'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 journal articles for your research on the topic 'Diagnostic imaging. Algorithms.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.
1
Chan, Wee-Shian. "Can pregnancy-adapted algorithms avoid diagnostic imaging for pulmonary embolism?" Hematology 2020, no. 1 (December 4, 2020): 184–89. http://dx.doi.org/10.1182/hematology.2020000105.
Full textAbstract:
Abstract The low prevalence of pulmonary embolism (PE) among pregnant patients presenting with suspected PE implies that most of these patients will be found not have the disease. Given this low prevalence, excluding PE in this population has necessitated the use of sensitive and specific diagnostic imaging, such as computed tomography pulmonary angiography or ventilation-perfusion scanning. Recent studies suggest that a clinical prediction rule with D-dimer testing can also be used to exclude a subset of pregnant patients with suspected PE without the need for diagnostic imaging. The YEARS criteria, which consist of clinical signs and symptoms of deep venous thrombosis, hemoptysis, and PE as the most likely diagnosis (a subjective variable), combined with selective D-dimer levels, seem to safely exclude up to one-third of these patients without imaging. The revised Geneva rule using objective variables, combined with nonpregnancy cutoffs for D-dimer levels, offers some promise, although fewer patients avoided imaging (14%). These recent studies provide evidence in support of radiation avoidance for some patients; however, for most, imaging remains the only option. Future studies should focus on improving the safety and techniques of imaging modalities, in addition to improving the specificity of D-dimer testing and objective prediction rules. Studies assessing patients’ and physicians’ values, preferences, and risk perceptions are also required to assist clinicians in shared decision making when counseling pregnant patients with suspected PE.
2
Sedláčková, Hana, Olga Dolejšová, Milan Hora, Jiří Ferda, Ondřej Hes, Ondřej Topolčan, Radka Fuchsová, and Radek Kučera. "Prostate Cancer Diagnostic Algorithm as a “Road Map” from the First Stratification of the Patient to the Final Treatment Decision." Life 11, no. 4 (April 7, 2021): 324. http://dx.doi.org/10.3390/life11040324.
Full textAbstract:
The diagnostics of prostate cancer are currently based on three pillars: prostate biomarker panel, imaging techniques, and histological verification. This paper presents a diagnostic algorithm that can serve as a “road map”: from initial patient stratification to the final decision regarding treatment. The algorithm is based on a review of the current literature combined with our own experience. Diagnostic algorithms are a feature of an advanced healthcare system in which all steps are consciously coordinated and optimized to ensure the proper individualization of the treatment process. The prostate cancer diagnostic algorithm was created using the prostate specific antigen and in particular the Prostate Health Index in the first line of patient stratification. It then continued on the diagnostic pathway via imaging techniques, biopsy, or active surveillance, and then on to the treatment decision itself. In conclusion, the prostate cancer diagnostic algorithm presented here is a functional tool for initial patient stratification, comprehensive staging, and aggressiveness assessment. Above all, emphasis is placed on the use of the Prostate Health Index (PHI) in the first stratification of the patients as a predictor of aggressiveness and clinical stage of prostrate cancer (PCa). The inclusion of PHI in the algorithm significantly increases the accuracy and speed of the diagnostic procedure and allows to choose the optimal pathway just from the beginning. The use of advanced diagnostic techniques allows us to move towards to a more advanced level of cancer care. This diagnostics algorithm has become a standard of care in our hospital. The algorithm is continuously validated and modified based on our results.
3
Huisman, Menno V., and Frederikus A. Klok. "Current challenges in diagnostic imaging of venous thromboembolism." Hematology 2015, no. 1 (December 5, 2015): 202–9. http://dx.doi.org/10.1182/asheducation-2015.1.202.
Full textAbstract:
Abstract Because the clinical diagnosis of deep-vein thrombosis and pulmonary embolism is nonspecific, integrated diagnostic approaches for patients with suspected venous thromboembolism have been developed over the years, involving both non-invasive bedside tools (clinical decision rules and D-dimer blood tests) for patients with low pretest probability and diagnostic techniques (compression ultrasound for deep-vein thrombosis and computed tomography pulmonary angiography for pulmonary embolism) for those with a high pretest probability. This combination has led to standardized diagnostic algorithms with proven safety for excluding venous thrombotic disease. At the same time, it has become apparent that, as a result of the natural history of venous thrombosis, there are special patient populations in which the current standard diagnostic algorithms are not sufficient. In this review, we present 3 evidence-based patient cases to underline recent developments in the imaging diagnosis of venous thromboembolism.
4
Huisman, Menno V., and Frederikus A. Klok. "Current challenges in diagnostic imaging of venous thromboembolism." Blood 126, no. 21 (November 19, 2015): 2376–82. http://dx.doi.org/10.1182/blood-2015-05-640979.
Full textAbstract:
Abstract Because the clinical diagnosis of deep-vein thrombosis and pulmonary embolism is nonspecific, integrated diagnostic approaches for patients with suspected venous thromboembolism have been developed over the years, involving both non-invasive bedside tools (clinical decision rules and D-dimer blood tests) for patients with low pretest probability and diagnostic techniques (compression ultrasound for deep-vein thrombosis and computed tomography pulmonary angiography for pulmonary embolism) for those with a high pretest probability. This combination has led to standardized diagnostic algorithms with proven safety for excluding venous thrombotic disease. At the same time, it has become apparent that, as a result of the natural history of venous thrombosis, there are special patient populations in which the current standard diagnostic algorithms are not sufficient. In this review, we present 3 evidence-based patient cases to underline recent developments in the imaging diagnosis of venous thromboembolism.
5
Yeo, Melissa, Bahman Tahayori, Hong Kuan Kok, Julian Maingard, Numan Kutaiba, Jeremy Russell, Vincent Thijs, et al. "Review of deep learning algorithms for the automatic detection of intracranial hemorrhages on computed tomography head imaging." Journal of NeuroInterventional Surgery 13, no. 4 (January 21, 2021): 369–78. http://dx.doi.org/10.1136/neurintsurg-2020-017099.
Full textAbstract:
Artificial intelligence is a rapidly evolving field, with modern technological advances and the growth of electronic health data opening new possibilities in diagnostic radiology. In recent years, the performance of deep learning (DL) algorithms on various medical image tasks have continually improved. DL algorithms have been proposed as a tool to detect various forms of intracranial hemorrhage on non-contrast computed tomography (NCCT) of the head. In subtle, acute cases, the capacity for DL algorithm image interpretation support might improve the diagnostic yield of CT for detection of this time-critical condition, potentially expediting treatment where appropriate and improving patient outcomes. However, there are multiple challenges to DL algorithm implementation, such as the relative scarcity of labeled datasets, the difficulties in developing algorithms capable of volumetric medical image analysis, and the complex practicalities of deployment into clinical practice. This review examines the literature and the approaches taken in the development of DL algorithms for the detection of intracranial hemorrhage on NCCT head studies. Considerations in crafting such algorithms will be discussed, as well as challenges which must be overcome to ensure effective, dependable implementations as automated tools in a clinical setting.
6
Hu, Yong, Jie Tang, Shenghao Zhao, and Ye Li. "Diffusion-Weighted Imaging-Magnetic Resonance Imaging Information under Class-Structured Deep Convolutional Neural Network Algorithm in the Prognostic Chemotherapy of Osteosarcoma." Scientific Programming 2021 (August 28, 2021): 1–12. http://dx.doi.org/10.1155/2021/4989166.
Full textAbstract:
In order to improve the efficiency of early imaging diagnosis of patients with osteosarcoma and the effect of neoadjuvant chemotherapy based on the results of imaging examinations, 48 patients with suspected osteosarcoma were selected as the research objects and their diffusion-weighted imaging (DWI)-magnetic resonance imaging (MRI) images were regularized in this study. Then, a DWI-MRI image discrimination model was established based on the class-structured deep convolutional neural network (CSDCNN) algorithm. The peak signal-to-noise ratio (PSNR), mean square error (MSE), and edge preserve index (EPI) were applied to evaluate the image quality after processing by the CSDCNN algorithm; the accuracy, recall rate, precise rate, and F1 score were employed to evaluate the diagnostic efficiency of CSDCNN algorithm; the apparent diffusion coefficient (ADC) was adopted to evaluate the therapeutic effect of neoadjuvant chemotherapy based on the CSDCNN algorithm, and SegNet, LeNet, and AlexNet algorithms were introduced for comparison. The results showed that the PSNR, MSE, and EPI values of DWI-MRI images of patients with osteosarcoma were 29.1941, 0.0016, and 0.9688, respectively, after using the CSDCNN algorithm to process the DWI-MRI images. The three indicators were significantly better than other algorithms, and the difference was statistically significant ( P < 0.05 ). According to the results of imaging diagnosis of patients with osteosarcoma, there was no significant difference between the assisted diagnosis effect of the CSDCNN algorithm and the pathological examination results ( P > 0.05 ). The results of adjuvant chemotherapy based on the CSDCNN algorithm found that the ADCmean value of the patients after chemotherapy was 1.66 ± 0.17 and the ADCmin value was 1.33 ± 0.15; the two indicators were significantly higher than other algorithms, and the difference was statistically significant ( P < 0.05 ). In conclusion, the CSDCNN algorithm had a good effect on DWI-MRI image processing of patients with osteosarcoma, which could improve the diagnostic accuracy of patients with osteosarcoma. Moreover, the diagnosis results based on this algorithm could achieve better neoadjuvant chemotherapy effects and assist clinicians in imaging diagnosis and clinical treatment of patients with osteosarcoma.
7
Wei, Wei, Liang Liu, Zhong Qin Hu, and Yu Jing Zhou. "Rigid Medical Image Registration Based on Genetic Algorithms and Mutual Information." Applied Mechanics and Materials 665 (October 2014): 712–17. http://dx.doi.org/10.4028/www.scientific.net/amm.665.712.
Full textAbstract:
With the variety of medical imaging equipment’s application in the medical process,medical image registration becomes particularly important in the field of medical image processing,which has important clinical diagnostic and therapeutic value. This article describes the matrix conversion method of the rigid registration model, the basic concepts and principles of the mutual information algorithm ,the basic idea of genetic algorithms and algorithm’s flow , and the application of the improved genetic algorithms in practice. The rigid registration of two CT brain bones images uses mutual information as a similarity measure, genetic algorithm as the search strategy and matlab as programming environment. Using the three-point crossover technique to exchange the three parameters in the rigid transformation repeectively to produce new individuals, the genetic algorithm’s local search ability enhanced and the prematurity phenomenon can be reduced through the depth study of the basic genetic algorithm. The experiments show that the registration has high stability and accuracy.
8
Robert-Ebadi, Helia, and Marc Righini. "Diagnosis of acute Pulmonary Embolism." Hämostaseologie 38, no. 01 (February 2018): 11–21. http://dx.doi.org/10.5482/hamo-17-07-0023.
Full textAbstract:
SummaryDuring the last three decades, considerable advances in the management of patients with suspected pulmonary embolism (PE) have improved diagnostic accuracy and made management algorithms safer, easier to use and well standardized. These diagnostic algorithms are mainly based on the assessment of clinical pretest probability, D-Dimer measurement and imaging tests, mainly computed tomography pulmonary angiography (CTPA). These diagnostic algorithms allow a safe and cost-effective diagnosis for most patients with suspected PE.In this review, we discuss current existing evidence for PE diagnosis, the challenge of diagnosing PE in special patient populations, as well as novel imaging tests for PE diagnosis.
9
Gődény, Mária, Éva Szabó, Mária Bidlek, Krisztina Fehér, Tímea Nagy, and Miklós Kásler. "Role of imaging in the diagnostic and therapeutic algorithms of breast cancer." Orvosi Hetilap 153, no. 1 (January 2012): 3–13. http://dx.doi.org/10.1556/oh.2012.29250.
Full textAbstract:
Early diagnosis and prevention have the most significant effect on overall disease specific outcome; 90% of all breast cancer cases could be cured if diagnosed early and treated accurately. As for all diagnostic methods the most important requirement for diagnostic imaging is to detect breast cancer in its early stage, and to determine accurate tumor staging, in order to select the appropriate therapy. Its role is to monitor the effectiveness of therapy, to follow up patients reliably for early detection of recurrent disease. The spectrum of radiological imaging methods in breast cancer became broader in the past two decades; imaging that provides functional or metabolic data and whole body information such as CT, MRI and PET-CT are now available besides common X-ray and ultrasound mammography. The MRI is getting more and more important for the detection and characterization of breast cancer. Multimodal imaging techniques provide more accurate analysis, which is confirmed by increasing statistics authentically, but none of the imaging methods was specific enough to provide histological diagnosis. However, imaging-guided biopsies enable precise histological or cytological confirmation. Orv. Hetil., 2012, 153, 3–13.
10
Lomoschitz, Fritz M., Edith Eisenhuber, Ken F. Linnau, Philipp Peloschek, Maria Schoder, and Alexander A. Bankier. "Imaging of chest trauma: radiological patterns of injury and diagnostic algorithms." European Journal of Radiology 48, no. 1 (October 2003): 61–70. http://dx.doi.org/10.1016/s0720-048x(03)00202-x.
Full text
11
Mens, T. E., L. M. Pol, N. Es, I. M. Bistervels, A. T. A. Mairuhu, T. Hulle, F. A. Klok, M. V. Huisman, and S. Middeldorp. "Sex‐specific performance of pre‐imaging diagnostic algorithms for pulmonary embolism." Journal of Thrombosis and Haemostasis 16, no. 5 (March 22, 2018): 858–65. http://dx.doi.org/10.1111/jth.13984.
Full text
12
Tanaka, Hidekazu, and Zahra Sharif Khodaei. "Reliability Assessment of SHM Methodologies for Damage Detection." Key Engineering Materials 713 (September 2016): 244–47. http://dx.doi.org/10.4028/www.scientific.net/kem.713.244.
Full textAbstract:
Probability-based imaging which illustrates a distribution map of probability of damage presence in structures is a diagnostic method well established for damage detection in sensorized structures. Since the quality of the recorded signal is directly linked to the reliability of the diagnostic outcome, the assessment of robustness of the damage detection methodology is of high significance. In this paper, robustness and reliability of the current probability based imaging algorithms have been assessed for detecting BVID in a composite panel. Consequently, a proposed outlier analysis and DI probability distribution damage detection algorithm was shown to improve the reliability of the detection method.
13
Racz, Heather, Karen Mills, Lan Vu, and Michael J. Kovacs. "The Diagnosis of Venous Thromboembolism (VTE) in the Emergency Room: Poor Compliance with Recommended Diagnostic Algorithms." Blood 106, no. 11 (November 16, 2005): 2243. http://dx.doi.org/10.1182/blood.v106.11.2243.2243.
Full textAbstract:
Abstract Background: The diagnosis of VTE remains problematic in the emergency room. There are a number of algorithms, for both pulmonary embolism (PE) and deep venous thrombosis (DVT), that have been validated for use. These incorporate clinical assessment of pretest probability, D-Dimer measurement, and non-invasive diagnostic imaging. The purpose of this study was to evaluate adherence to the VTE diagnostic algorithms (according to Wells, Anderson et al.) at Victoria Hospital, London Ontario (a tertiary centre). Methods: The charts for all patients who presented with suspected DVT or PE during a two-month period were retrospectively reviewed. Patients were identified by those who had D-dimer testing or diagnostic imaging for VTE (D-dimers are only indicated for use in our hospital for the investigation of VTE). Patients were excluded if they were currently anticoagulated, pregnant, had upper limb DVT or were <18 years of age. All charts were reviewed by 3 persons to assign the Wells criteriae and to review the adherence to the recommended algorithms - determination was by consensus. Results: There were 289 patients included, 157 women and 132 men with an average age of 57. Of 289 patients included, 242 were investigated for PE with 6 events occurring, for an event rate of 2.5%. Forty-seven patients were investigated for DVT, with 4 events, for an event rate of 8.5%. The algorithms were seemingly correctly applied at superficial analysis in 64.4% of all patients and incorrectly applied in 20.8% of all patients. In 14.9% of patients, the algorithms were not followed to completion due to admission to hospital or an alternative diagnosis developing. Consultants correctly managed in 68.37% of cases and Residents in 59.8%. Although 71% of patients with suspected PE were seemingly managed according to algorithm - the vast majority of these patients had a low pretest probability (217) and were investigated with D-dimer only, which was negative. There were 25 patients in the moderate to high probability group and 17 were incorrectly managed with either unnecessary D-dimer assessments or a lack of leg imaging after non-diagnostic V/Q scans or CT scans. Eight patients in the low probability group had imaging despite negative D-dimer tests. With an event rate of only 2.5%, a disproportionately large number of patients were investigated for PE. Only 30% of patients with suspected DVT were managed correctly according to algorithm, 41% for “unlikely” and 7% “likely”. Of the 32 patients in the “unlikely” group, 9 patients had U/S performed despite negative D-dimer and 5 patients had U/S without D-dimer assessment. For the 15 patients who were “likely”, 6 had D-dimers performed upfront and 6 did not have D-dimers done after initial negative imaging. Overall, of 46 patients who had chest imaging for PE, 13 V/Q scans and 1 CT scan were done that were not indicated and 7 patients who should have been imaged were not. In the DVT group, 39 U/S were done and 10 of these were not indicated. Conclusions: The disproportionate amount of PE patients, and the overall low event rate for PE, suggest that D-dimers are being used indiscriminately as a screening test for the diagnosis of chest symptoms, an approach that has not been validated by studies. The algorithms for the diagnosis of DVT and PE are not being applied appropriately at our centre. The implications of this include the potential for missed diagnoses as well as the cost and potential clinical consequences of over investigation.
14
Vestrum, Robert W., Don C. Lawton, and Ron Schmid. "Imaging structures below dipping TI media." GEOPHYSICS 64, no. 4 (July 1999): 1239–46. http://dx.doi.org/10.1190/1.1444630.
Full textAbstract:
Seismic anisotropy in dipping shales causes imaging and positioning problems for underlying structures. We developed an anisotropic depth‐migration approach for P-wave seismic data in transversely isotropic (TI) media with a tilted axis of symmetry normal to bedding. We added anisotropic and dip parameters to the depth‐imaging velocity model and used prestack depth‐migrated image gathers in a diagnostic manner to refine the anisotropic velocity model. The apparent position of structures below dipping anisotropic overburden changes considerably between isotropic and anisotropic migrations. The ray‐tracing algorithm used in a 2-D prestack Kirchhoff depth migration was modified to calculate traveltimes in the presence of TI media with a tilted symmetry axis. The resulting anisotropic depth‐migration algorithm was applied to physical‐model seismic data and field seismic data from the Canadian Rocky Mountain Thrust and Fold Belt. The anisotropic depth migrations offer significant improvements in positioning and reflector continuity over those obtained using isotropic algorithms.
15
van Erkel, Arian R., and Peter M. T. Pattynama. "Cost-effective diagnostic Algorithms in pulmonary embolism: An updated analysis." Academic Radiology 5 (September 1998): S321—S327. http://dx.doi.org/10.1016/s1076-6332(98)80344-9.
Full text
16
Wen, Cathlyn Y., and Robert J. Beaton. "Subjective Image Quality Evaluation of Image Compression Techniques." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 40, no. 23 (October 1996): 1188–92. http://dx.doi.org/10.1177/154193129604002309.
Full textAbstract:
Image compression reduces the amount of data in digital images and, therefore, allows efficient storage, processing, and transmission of pictorial information. However, compression algorithms can degrade image quality by introducing artifacts, which may be unacceptable for users' tasks. This work examined the subjective effects of JPEG and wavelet compression algorithms on a series of medical images. Six digitized chest images were processed by each algorithm at various compression levels. Twelve radiologists rated the perceived image quality of the compressed images relative to the corresponding uncompressed images, as well as rated the acceptability of the compressed images for diagnostic purposes. The results indicate that subjective image quality and acceptability decreased with increasing compression levels; however, all images remained acceptable for diagnostic purposes. At high compression ratios, JPEG compressed images were judged less acceptable for diagnostic purposes than the wavelet compressed images. These results contribute to emerging system design guidelines for digital imaging workstations.
17
Stich, Manuel, Jeannine Vogt, Michaela Lindner, and Ralf Ringler. "Implementation and evaluation of segmentation algorithms according to multimodal imaging in personalized medicine." Current Directions in Biomedical Engineering 3, no. 2 (September 7, 2017): 207–10. http://dx.doi.org/10.1515/cdbme-2017-0178.
Full textAbstract:
AbstractMultimodal imaging is gaining in importance in the field of personalized medicine and can be described as a current trend in medical imaging diagnostics. The segmentation, classification and analysis of tissue structures is essential. The goal of this study is the evaluation of established segmentation methods on different medical image data sets acquired with different diagnostic procedures. Established segmentation methods were implemented using the latest state of the art and applied to medical image data sets. In order to benchmark the segmentation performance quantitatively, medical image data sets were superimposed with artificial Gaussian noise, and the mis-segmentation as a function of the image SNR or CNR was compared to a gold standard. The evaluation of the image segmentation showed that the best results of pixel-based segmentation (< 3%) can be achieved with methods of machine learning, multithreshold and advanced level-set method - even at high artificial noise (SNR< 18). Finally, the complexity of the object geometry and the contrast of the ROI to the surrounding tissue must also be considered to select the best segmentation algorithm.
18
Li, Yousheng, and Guitao Xia. "Multioperator Algorithm-Based Ultrasound Imaging Combined with Hysteroscopy for the Diagnosis of Endometrial Polyps." Scientific Programming 2021 (August 4, 2021): 1–9. http://dx.doi.org/10.1155/2021/1808665.
Full textAbstract:
This study aimed to explore the diagnosis of endometrial polyps (EMP) by ultrasound imaging based on multi-operator algorithms combined with hysteroscopy. This study is the first to investigate the resolution of the ultrasound adaptive beamforming algorithm (MOAD), after which the proposed algorithm was applied to ultrasound diagnosis of 102 patients with EMP and pathologically diagnosed with vaginal irregular bleeding, and the evaluation efficacy of the MOAD algorithm based on EMP was compared. The resolution of the MOAD-based imaging algorithm (0.0645) was significantly lower than that of the diagonal loading operator (0.1475), the symbol coherence coefficient operator (0.1342), and the generalized coherence factor operator (0.1234), with significant differences ( P < 0.05 ). The proportion of patients with EMP aged 46–55 years was the largest (55.9%). There were 64 cases of EMP that produced complications, of which the proportion of patients with uterine fibroids (41.52%), abnormal uterine bleeding (76.24%), and menstrual changes (42.57%) was relatively large. Patients with nonfunctioning polyps accounted for the largest proportion (84.46%), followed by those with basal polyps (76.24%), and the difference was statistically significant ( P < 0.05 ). The positive cases of EMP detected by ultrasound imaging (38 cases) were significantly lower than those with pathological diagnosis (94 cases), and the difference was statistically significant ( P < 0.05 ). The SE, SP, FNR, and FPR of EMP diagnosed by ultrasound imaging combined with hysteroscopy were 64.45%, 84.67%, 35.48%, and 13.36%, respectively. It has high diagnostic value compared with single ultrasound imaging diagnosis, and the difference was statistically significant ( P < 0.05 ). In conclusion, the imaging based on the MOAD algorithm is obvious and the pixel resolution can be successfully improved. The diagnostic value of ultrasound combined with hysteroscopy for EMP was better than that of ultrasound alone ( P < 0.05 ), and it had a high diagnostic value.
19
Dao-Ngoc, Lam, and Yi-Chun Du. "Generative Noise Reduction in Dental Cone-Beam CT by a Selective Anatomy Analytic Iteration Reconstruction Algorithm." Electronics 8, no. 12 (November 21, 2019): 1381. http://dx.doi.org/10.3390/electronics8121381.
Full textAbstract:
Dental cone-beam computed tomography (CBCT) is a powerful tool in clinical treatment planning, especially in a digital dentistry platform. Currently, the “as low as diagnostically acceptable” (ALADA) principle and diagnostic ability are a trade-off in most of the 3D integrated applications, especially in the low radio-opaque densified tissue structure. The CBCT benefits in comprehensive diagnosis and its treatment prognosis for post-operation predictability are clinically known in modern dentistry. In this paper, we propose a new algorithm called the selective anatomy analytic iteration reconstruction (SA2IR) algorithm for the sparse-projection set. The algorithm was simulated on a phantom structure analogous to a patient’s head for geometric similarity. The proposed algorithm is projection-based. Interpolated set enrichment and trio-subset enhancement were used to reduce the generative noise and maintain the scan’s clinical diagnostic ability. The results show that proposed method was highly applicable in medico-dental imaging diagnostics fusion for the computer-aided treatment planning, because it had significant generative noise reduction and lowered computational cost when compared to the other common contemporary algorithms for sparse projection, which generate a low-dosed CBCT reconstruction.
20
Busko, Ekaterina, Anastasiya Goncharova, Nadezhda Rozhkova, Vladislav Semiglazov, Alena Shishova, Elena Zhiltsova, Grigory Zinovev, Kseniya Beloborodova, and Petr Krivorotko. "Model for making diagnostic decisions in multiparametric ultrasound of breast lesions." Problems in oncology 66, no. 6 (December 30, 2020): 653–58. http://dx.doi.org/10.37469/0507-3758-2020-66-6-653-658.
Full textAbstract:
In order to standardize the description of the breast imaging, the BI-RADS (Breast Imaging Reporting And Data System) imaging system developed by the American College of Radiologists ACR is widely used in world practice. At the same time, numerous visual characteristics of breast lesions with different diagnostic methods complicate the adoption of diagnostic decisions while using the BI-RADS system. The greatest difficulties arise when assessing a variety of multiparametric ultrasound signs of diseases. In this regard, in order to increase the efficiency of these technologies and make fast diagnostic decisions, it becomes relevant to develop a system model based on algorithms using the BI-RADS lexicon.
Materials and methods: from 2017 to 2019 on the basis of the Research Oncology Center named after N.N. Petrov 277 women with various complaints of breast disease were examined using multiparametric ultrasound with elastography and contrast enhancement (2.5 ml Sonovue) on a Hitachi Hi Vision Ascendus ultrasound scanner. The software implementation of the diagnostic decision-making model was carried out using the C # programming language using the Microsoft Visual integrated development environment.
Results: The effectiveness of the developed diagnostic model using the optimal algorithm for the use of various ultrasound technologies in determining the malignancy of the formation showed Sensitivity (Se) = 90.8%, Specificity (Sp) = 95.5%, Positive Predictive Value (PPV) = 88.5%, Negative Predictive Value (NPV) = 96.4%, Accuracy (Ac) = 94.2%. The effectiveness of the developed model in grouping diseases showed Se = 84.2%, Sp = 81.1%, PPV = 62.7%, NPV = 93.1%, Ac = 81.9%.
Conclusions: The proposed system model of the optimal algorithm for making a diagnostic decision based on statistically significant multiparametric ultrasound signs increases the diagnostic efficiency.
21
Xuan, Jianhua, Uwe Klimach, Hongzhi Zhao, Qiushui Chen, Yingyin Zou, and Yue Wang. "Improved Diagnostics Using Polarization Imaging and Artificial Neural Networks." International Journal of Biomedical Imaging 2007 (2007): 1–11. http://dx.doi.org/10.1155/2007/74143.
Full textAbstract:
In recent years, there has been an increasing interest in studying the propagation of polarized light in biological cells and tissues. This paper presents a novel approach to cell or tissue imaging using a full Stokes imaging system with advanced polarization image analysis algorithms for improved diagnostics. The key component of the Stokes imaging system is the electrically tunable retarder, enabling high-speed operation of the system to acquire four intensity images sequentially. From the acquired intensity images, four Stokes vector images can be computed to obtain complete polarization information. Polarization image analysis algorithms are then developed to analyze Stokes polarization images for cell or tissue classification. Specifically, wavelet transforms are first applied to the Stokes components for initial feature analysis and extraction. Artificial neural networks (ANNs) are then used to extract diagnostic features for improved classification and prediction. In this study, phantom experiments have been conducted using a prototyped Stokes polarization imaging device. In particular, several types of phantoms, consisting of polystyrene latex spheres in various diameters, were prepared to simulate different conditions of epidermal layer of skin. The experimental results from phantom studies and a plant cell study show that the classification performance using Stokes images is significantly improved over that using the intensity image only.
22
Le Gal, Grégoire, Henri Bounameaux, and Marc Righini. "Venous thromboembolism diagnosis: unresolved issues." Thrombosis and Haemostasis 113, no. 06 (November 2015): 1184–92. http://dx.doi.org/10.1160/th14-06-0530.
Full textAbstract:
SummaryRecent advances in the management of patients with suspected VTE have both improved diagnostic accuracy and made management algorithms safer, easier to use and well standardised. These diagnostic algorithms are mainly based on the assessment of clinical pretest probability, D-dimer measurement and imaging tests, mainly represented by compression ultrasound (CUS) for suspected DVT and computed tomography pulmonary angiography (CTPA) or lung ventilationperfusion scan for pulmonary embolism. These diagnostic algorithms allow a safe and cost-effective diagnosis for most patients with suspected VTE. In this review, we focus on the challenge of diagnosing VTE in special patient populations, such as elderly patients, pregnant women, or patients with a prior VTE. Some additional challenges are arising that might require adjustments to current diagnostic strategies, such as the reduced clinical suspicion threshold, resulting in a lower proportion of VTE among suspected patients; the overdiagnosis and overtreatment of VTE, especially regarding calf deep-vein thrombosis (DVT) and subsegmental pulmonary embolism (SSPE).
23
Pfob, André, Chris Sidey-Gibbons, Marios Konstantinos Tasoulis, Han-Byoel Lee, Vivian Koelbel, Henry Mark Kuerer, and Joerg Heil. "Artificial intelligence to accurately identify breast cancer patients with a pathologic complete response for omission of surgery after neoadjuvant systemic therapy: An international multicenter analysis." Journal of Clinical Oncology 38, no. 15_suppl (May 20, 2020): 565. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.565.
Full textAbstract:
565 Background: Neoadjuvant systemic treatment elicits a pathologic complete response (pCR) in up to 80% of women with breast cancer. In such cases, breast surgery, the gold standard for confirming pCR in the breast, may be considered overtreatment. So far, no approach alone – e.g. imaging, vacuum-assisted biopsy (VAB) – has accurately detected and excluded residual disease without surgery in multicenter prospective trials. We evaluated the ability of Artificial Intelligence algorithms to securely identify patients with residual tumor in the breast to safely select patients who might be spared from surgery. Methods: We collected multicenter, international data from 570 women who were included in prospective trials with initial stage I-III breast cancer of all biological subtypes and at least partial response on imaging, undergoing VAB before guideline-adherent surgery. We trained an ensemble of algorithms (including Regularized Regression, Support Vector Machines, and Neural Network) using 27 patient, tumor and VAB variables. Data were randomly partitioned into training and test sample with a 3:1 ratio and developed with 10-fold cross-validation. Primary endpoint was the sensitivity to diagnose residual disease by algorithm compared to surgery. Diagnostic performance of the algorithm was further evaluated on an external, independent dataset. Results: The algorithm was able to reliably identify women with residual disease before surgery (see table): Sensitivity for the internal test set was 96.9% (94 of 97; 95%CI 91.2-99.4%) and for the external, independent dataset 96.2% (26 of 27; 95%CI 80.4-99.9%). Most informative predictor of residual disease were tumor cells diagnosed in the VAB specimen, DCIS in the initial diagnostic biopsy, grading, and largest diameter on imaging after neoadjuvant treatment. Conclusions: Safely selected patients without residual disease as assessed by our algorithm may be spared by breast surgery in future trials. [Table: see text]
24
Nair, A., J. C. L. Rodrigues, S. Hare, A. Edey, A. Devaraj, J. Jacob, A. Johnstone, R. McStay, Erika Denton, and G. Robinson. "A British Society of Thoracic Imaging statement: considerations in designing local imaging diagnostic algorithms for the COVID-19 pandemic." Clinical Radiology 75, no. 5 (May 2020): 329–34. http://dx.doi.org/10.1016/j.crad.2020.03.008.
Full text
25
Sadro, Claudia T. "Imaging the Endometrium: A Pictorial Essay." Canadian Association of Radiologists Journal 67, no. 3 (August 2016): 254–62. http://dx.doi.org/10.1016/j.carj.2015.09.012.
Full textAbstract:
Female gynaecologic conditions arising from the endometrium are common and depend on a woman's age, her menstrual history, and the use of medications such as hormone replacement and tamoxifen. Both benign and malignant conditions affect the endometrium. Benign conditions must be distinguished from malignant and premalignant conditions. The most commonly used imaging modality for evaluating the endometrium is pelvic ultrasound with transabdominal and transvaginal techniques. Additional imaging methods include hysterosonography and magnetic resonance imaging. This pictorial essay will review the normal and abnormal appearance of the endometrium and diagnostic algorithms to evaluate abnormal vaginal bleeding and abnormal endometrial thickness.
26
Noël, Peter B., Stephan Engels, Thomas Köhler, Daniela Muenzel, Daniela Franz, Michael Rasper, Ernst J. Rummeny, Martin Dobritz, and Alexander A. Fingerle. "Evaluation of an iterative model-based CT reconstruction algorithm by intra-patient comparison of standard and ultra-low-dose examinations." Acta Radiologica 59, no. 10 (January 10, 2018): 1225–31. http://dx.doi.org/10.1177/0284185117752551.
Full textAbstract:
Background The explosive growth of computer tomography (CT) has led to a growing public health concern about patient and population radiation dose. A recently introduced technique for dose reduction, which can be combined with tube-current modulation, over-beam reduction, and organ-specific dose reduction, is iterative reconstruction (IR). Purpose To evaluate the quality, at different radiation dose levels, of three reconstruction algorithms for diagnostics of patients with proven liver metastases under tumor follow-up. Material and Methods A total of 40 thorax–abdomen–pelvis CT examinations acquired from 20 patients in a tumor follow-up were included. All patients were imaged using the standard-dose and a specific low-dose CT protocol. Reconstructed slices were generated by using three different reconstruction algorithms: a classical filtered back projection (FBP); a first-generation iterative noise-reduction algorithm (iDose4); and a next generation model-based IR algorithm (IMR). Results The overall detection of liver lesions tended to be higher with the IMR algorithm than with FBP or iDose4. The IMR dataset at standard dose yielded the highest overall detectability, while the low-dose FBP dataset showed the lowest detectability. For the low-dose protocols, a significantly improved detectability of the liver lesion can be reported compared to FBP or iDose4 ( P = 0.01). The radiation dose decreased by an approximate factor of 5 between the standard-dose and the low-dose protocol. Conclusion The latest generation of IR algorithms significantly improved the diagnostic image quality and provided virtually noise-free images for ultra-low-dose CT imaging.
27
Zohaib, Ali, Muhammad Hamid Saeed, Shaukat Ali Shahid, Muhammad Shahbaz, Mudassar Iqbal, and Faisal Ehsan. "MYOCARDIAL PERFUSION IMAGING (MPI)." Professional Medical Journal 23, no. 04 (April 10, 2016): 451–59. http://dx.doi.org/10.29309/tpmj/2016.23.04.1504.
Full textAbstract:
Objective: Myocardial perfusion imaging (MPI) with superior quality of imagesin least acquisition time is imperative for diagnostic purpose. The objective of this study wasto compare the Filter Back Projection (FBP) and half time Astonish reconstruction techniquesin diagnosis of coronary artery disease using cardiac catheterization as gold standard. Placeand period of study: Study was conducted in nuclear cardiology department, at Faisalabadinstitute of cardiology, Faisalabad from November 2014 to July2015. Material & Methods:A total of 60patients (56 + 19years) underwent gated MPI with Tc-99m Sestamibi and 30patients of these underwent cardiac catheterization as well. Images were reconstructed withhalf time Astonish and FBP algorithms. CAD detection, LVEF, perfusion defect comparisonusing polar maps and diagnostic performance were calculated. Results: Perfusion defectscalculated through Astonish and FBP techniques were compared and correlated with coronaryangiogram. The sensitivity, specificity and accuracy for detection of CAD in vascular territories(LAD, LCX & RCA) of the patients were 72%, 41% and 57% with FBP and 86%, 54% and 71%with Astonish. The calculated LVEF showed good correlation (r = 0.8773) between Astonishand cardiac catheterization. Conclusion: There were no significant changes in image quality ofHalf-time Astonish compared to full-time FBP. Astonish reconstruction showed equal resolution,reduced background noise and radiation dose. Reduced scanning time will improve patientscan quality due to less chance of attenuation.
28
E. A. Armya Armya, Revella, and Adnan Mohsin Abdulazeez. "Medical Images Segmentation Based on Unsupervised Algorithms: A Review." Qubahan Academic Journal 1, no. 2 (April 28, 2021): 71–80. http://dx.doi.org/10.48161/qaj.v1n2a51.
Full textAbstract:
Medical image segmentation plays an essential role in computer-aided diagnostic systems in various applications. Therefore, researchers are attracted to apply new algorithms for medical image processing because it is a massive investment in developing medical imaging methods such as dermatoscopy, X-rays, microscopy, ultrasound, computed tomography (CT), positron emission tomography, and magnetic resonance imaging. (Magnetic Resonance Imaging), So segmentation of medical images is considered one of the most important medical imaging processes because it extracts the field of interest from the Return on investment (ROI) through an automatic or semi-automatic process. The medical image is divided into regions based on the specific descriptions, such as tissue/organ division in medical applications for border detection, tumor detection/segmentation, and comprehensive and accurate detection. Several methods of segmentation have been proposed in the literature, but their efficacy is difficult to compare. To better address, this issue, a variety of measurement standards have been suggested to decide the consistency of the segmentation outcome. Unsupervised ranking criteria use some of the statistics in the hash score based on the original picture. The key aim of this paper is to study some literature on unsupervised algorithms (K-mean, K-medoids) and to compare the working efficiency of unsupervised algorithms with different types of medical images.
29
Paixao, Charlinne, Jean-Philippe Lustig, Sylvain Causeret, Loic Chaigneau, Alexis Danner, and Sebastien Aubry. "Tumors and pseudotumors of the soft tissues: Imaging semiology and strategy." Journal of Clinical Imaging Science 11 (March 3, 2021): 13. http://dx.doi.org/10.25259/jcis_135_2020.
Full textAbstract:
The aims of this educational review are to learn the semiological basis of soft-tissue lesions and, with the help of diagnostic algorithms, to apply the current recommendations for the management of soft-tissue tumors. Pseudotumors must first be identified and excluded. Among primary tumors, the search for macroscopic fat content on MRI is decisive; since it restricts the diagnostic range to adipocytic tumors. Key imaging features of non-adipocytic tumors are highlighted. When a deep soft-tissue mass is found, therapeutic abstention or simple monitoring is only appropriate when there is diagnostic certainty: This is only the case for typical pseudotumors, typical benign tumors, and fat tumors without atypical criteria. In all other cases, histological evidence is required. If there is any suspicion of soft-tissue sarcoma or any undetermined lesion, the patient should be referred to a sarcoma referral center before biopsy.
30
Weiß, Jakob, Christoph Schabel, Malte Bongers, Rainer Raupach, Stephan Clasen, Mike Notohamiprodjo, Konstantin Nikolaou, and Fabian Bamberg. "Impact of iterative metal artifact reduction on diagnostic image quality in patients with dental hardware." Acta Radiologica 58, no. 3 (July 20, 2016): 279–85. http://dx.doi.org/10.1177/0284185116646144.
Full textAbstract:
Background Metal artifacts often impair diagnostic accuracy in computed tomography (CT) imaging. Therefore, effective and workflow implemented metal artifact reduction algorithms are crucial to gain higher diagnostic image quality in patients with metallic hardware. Purpose To assess the clinical performance of a novel iterative metal artifact reduction (iMAR) algorithm for CT in patients with dental fillings. Material and Methods Thirty consecutive patients scheduled for CT imaging and dental fillings were included in the analysis. All patients underwent CT imaging using a second generation dual-source CT scanner (120 kV single-energy; 100/Sn140 kV in dual-energy, 219 mAs, gantry rotation time 0.28–1/s, collimation 0.6 mm) as part of their clinical work-up. Post-processing included standard kernel (B49) and an iterative MAR algorithm. Image quality and diagnostic value were assessed qualitatively (Likert scale) and quantitatively (HU ± SD) by two reviewers independently. Results All 30 patients were included in the analysis, with equal reconstruction times for iMAR and standard reconstruction (17 s ± 0.5 vs. 19 s ± 0.5; P > 0.05). Visual image quality was significantly higher for iMAR as compared with standard reconstruction (3.8 ± 0.5 vs. 2.6 ± 0.5; P < 0.0001, respectively) and showed improved evaluation of adjacent anatomical structures. Similarly, HU-based measurements of degree of artifacts were significantly lower in the iMAR reconstructions as compared with the standard reconstruction (0.9 ± 1.6 vs. –20 ± 47; P < 0.05, respectively). Conclusion The tested iterative, raw-data based reconstruction MAR algorithm allows for a significant reduction of metal artifacts and improved evaluation of adjacent anatomical structures in the head and neck area in patients with dental hardware.
31
Khan, T., T. Lopez, T. Khan, A. Ali, S. Syed, P. Patil, and A. Hatoum. "Re: a British Society of Thoracic Imaging statement: considerations in designing local imaging diagnostic algorithms for the COVID-19 pandemic." Clinical Radiology 75, no. 8 (August 2020): 636. http://dx.doi.org/10.1016/j.crad.2020.05.009.
Full text
32
Kainberger, Franz, Heinrich Czembirek, Franz Frühwald, Peter Pokieser, and Herwig Imhof. "Guidelines and algorithms: strategies for standardization of referral criteria in diagnostic radiology." European Radiology 12, no. 3 (March 2002): 673–79. http://dx.doi.org/10.1007/s003300101109.
Full text
33
Khazal, Shimaa Abdulsalam, and Mohammed Hussein Ali. "Increasing the Performance of the Iterative Computed Tomography Image Reconstruction Algorithms." Al-Nahrain Journal for Engineering Sciences 23, no. 2 (September 18, 2020): 194–203. http://dx.doi.org/10.29194/njes.23020194.
Full textAbstract:
Computed tomography (CT) imaging is an important diagnostic tool. CT imaging facilitates the internal rendering of a scanned object by measuring the attenuation of beams of X-ray radiation. CT employs a mathematical technique of image reconstruction; those techniques are classified as; analytical and iterative. The iterative reconstruction (IR) methods have been proven to be superior over the analytical methods, but due to their prolonged reconstruction time, those methods are excluded from routine use in clinical applications. In this paper the reconstruction time of an IR algorithm is minimized through the employment of an adaptive region growing segmentation method that focuses the image reconstruction process on a specified region, thus ignoring unwanted pixels that increase the computation time. This method is tested on the iterative algebraic reconstruction technique (ART) algorithm. Some phantom images are used in this paper to demonstrate the effects of the segmentation process. The simulation results are executed using MATLAB (version R2018b) programming language, and a computer system with the following specifications: CPU core i7 (2.40 GHz) for processing. Simulation results indicate that this method will reduce the reconstruction time of the iterative algorithms, and will enhance the quality of the reconstructed image.
34
Tran, Thuy Duong, and Ngoc Ha Bui. "Evaluation of image reconstruction algorithms in cone-beam computed tomography technique." Nuclear Science and Technology 9, no. 4 (September 3, 2021): 41–47. http://dx.doi.org/10.53747/jnst.v9i4.136.
Full textAbstract:
Cone-beam computed tomography (CBCT) technique is largely used in medical diagnostic imaging and nondestructive materials testing, especially in cases which require fast times and high accuracy level. In this paper, the pros and cons of Feldkamp-Davis-Kress (FDK) and simultaneous iterative reconstruction technique (SIRT) algorithms used in CBCT technique is studied. The method of simulating CBCT systems is also used to provide richer projection data, which helps the research to evaluate many aspects of algorithms.
35
Pykov, M. I., and Anastasia M. Vrublevskaya. "ECHOGRAPHY IN THE DIAGNOSTICS OF INFLAMMATORY BOWEL DISEASES IN CHILDREN." Russian Journal of Pediatric Surgery 24, no. 2 (May 12, 2020): 101–7. http://dx.doi.org/10.18821/1560-9510-2020-24-2-101-107.
Full textAbstract:
Crohn’s disease (CD) and ulcerative colitis (UC) are pathologies that have various clinical manifestations, which sometimes cause problems in putting a correct diagnosis by clinicians. The review of domestic and foreign literature highlighted the relevance in improving the diagnostics of inflammatory bowel disease (IBD). Modern diagnostic techniques (computed tomography, magnetic resonance imaging, various endoscopic and radiological methods) are widespread in clinical practice, but they have a number of limitations in pediatric practice and are associated with certain risks. Significant drawbacks are radiation loading at the child’s organism and general anesthesia. So, a diagnostic tool which provides sufficient information, widely available, safe and non-invasive is a need . The ultrasound examination meets all the above mentioned demands. Unfortunately, currently there are no explicit protocols to be used for ultrasound examination of children with CD and UC. Researches in this direction should be continued, so as to confirm the effectiveness of this technique in diagnosing the intestinal tube pathology and to develop algorithms for practical application of this imaging technique, particular in pediatric patients with IBD.
36
Ebdrup, Bjørn H., Martin C. Axelsen, Nikolaj Bak, Birgitte Fagerlund, Bob Oranje, Jayachandra M. Raghava, Mette Ø. Nielsen, Egill Rostrup, Lars K. Hansen, and Birte Y. Glenthøj. "Accuracy of diagnostic classification algorithms using cognitive-, electrophysiological-, and neuroanatomical data in antipsychotic-naïve schizophrenia patients." Psychological Medicine 49, no. 16 (December 18, 2018): 2754–63. http://dx.doi.org/10.1017/s0033291718003781.
Full textAbstract:
AbstractBackgroundA wealth of clinical studies have identified objective biomarkers, which separate schizophrenia patients from healthy controls on a group level, but current diagnostic systems solely include clinical symptoms. In this study, we investigate if machine learning algorithms on multimodal data can serve as a framework for clinical translation.MethodsForty-six antipsychotic-naïve, first-episode schizophrenia patients and 58 controls underwent neurocognitive tests, electrophysiology, and magnetic resonance imaging (MRI). Patients underwent clinical assessments before and after 6 weeks of antipsychotic monotherapy with amisulpride. Nine configurations of different supervised machine learning algorithms were applied to first estimate the unimodal diagnostic accuracy, and next to estimate the multimodal diagnostic accuracy. Finally, we explored the predictability of symptom remission.ResultsCognitive data significantly classified patients from controls (accuracies = 60–69%;pvalues = 0.0001–0.009). Accuracies of electrophysiology, structural MRI, and diffusion tensor imaging did not exceed chance level. Multimodal analyses with cognition plus any combination of one or more of the remaining three modalities did not outperform cognition alone. None of the modalities predicted symptom remission.ConclusionsIn this multivariate and multimodal study in antipsychotic-naïve patients, only cognition significantly discriminated patients from controls, and no modality appeared to predict short-term symptom remission. Overall, these findings add to the increasing call for cognition to be included in the definition of schizophrenia. To bring about the full potential of machine learning algorithms in first-episode, antipsychotic-naïve schizophrenia patients, carefula priorivariable selection based on independent data as well as inclusion of other modalities may be required.
37
Sagun, Matthew, Budi Kusnoto, Carla A. Evans, Maria Therese Galang-Boquiren, Grace Viana, and Ales Obrez. "Evaluation of Ricketts' and Bolton's growth prediction algorithms embedded in two diagnostic imaging and cephalometric software." Journal of the World Federation of Orthodontists 4, no. 4 (December 2015): 146–50. http://dx.doi.org/10.1016/j.ejwf.2015.10.002.
Full text
38
Mistry, Niraj, Rasha Abdel-Fahim, Amal Samaraweera, Olivier Mougin, Emma Tallantyre, Christopher Tench, Tim Jaspan, Peter Morris, Paul S. Morgan, and Nikos Evangelou. "Imaging central veins in brain lesions with 3-T T2*-weighted magnetic resonance imaging differentiates multiple sclerosis from microangiopathic brain lesions." Multiple Sclerosis Journal 22, no. 10 (July 19, 2016): 1289–96. http://dx.doi.org/10.1177/1352458515616700.
Full textAbstract:
Background: White matter lesions are frequently detected using brain magnetic resonance imaging (MRI) performed for various indications. Most are microangiopathic, but demyelination, including multiple sclerosis (MS), is an important cause; conventional MRI cannot always distinguish between these pathologies. The proportion of lesions with a central vein on 7-T T2*-weighted MRI prospectively distinguishes demyelination from microangiopathic lesions. Objective: To test whether 3-T T2*-weighted MRI can differentiate MS from microangiopathic brain lesions. Methods: A total of 40 patients were studied. Initially, a test cohort of 10 patients with MS and 10 patients with microangiopathic white matter lesions underwent 3-T T2*-weighted brain MRI. Anonymised scans were analysed blind to clinical data, and simple diagnostic rules were devised. These rules were applied to a validation cohort of 20 patients (13 with MS and 7 with microangiopathic lesions) by a blinded observer. Results: Within the test cohort, all patients with MS had central veins visible in >45% of brain lesions, while the rest had central veins visible in <45% of lesions. By applying diagnostic rules to the validation cohort, all remaining patients were correctly categorised. Conclusion: 3-T T2*-weighted brain MRI distinguishes perivenous MS lesions from microangiopathic lesions. Clinical application of this technique could supplement existing diagnostic algorithms.
39
Lippi, Giuseppe, and Mario Plebani. "Integrated diagnostics." Biochemia medica 30, no. 1 (February 15, 2020): 18–30. http://dx.doi.org/10.11613/bm.2020.010501.
Full textAbstract:
The current scenario of in vitro and in vivo diagnostics can be summarized using the “silo metaphor”, where laboratory medicine, pathology and radiology are three conceptually separated diagnostic disciplines, which will increasingly share many comparable features. The substantial progresses in our understanding of biochemical-biological interplays that characterize many human diseases, coupled with extraordinary technical advances, are now generating important multidisciplinary convergences, leading the way to a new frontier, called integrated diagnostics. This new discipline, which is currently defined as convergence of imaging, pathology and laboratory tests with advanced information technology, has an enormous potential for revolutionizing diagnosis and therapeutic management of human diseases, including those causing the largest number of worldwide deaths (i.e. cardiovascular disease, cancer and infectious diseases). However, some important drawbacks should be overcome, mostly represented by insufficient information technology infrastructures, costs and enormous volume of different information that will be integrated and delivered. To overcome these hurdles, some specific strategies should be defined and implemented, such as planning major integration of exiting information systems or developing innovative ones, combining bioinformatics and imaging informatics, using health technology assessment for assessing cost and benefits, providing interpretative comments in integrated reports, developing and using expert systems and neural networks, overcoming cultural and political boundaries for generating multidisciplinary teams and integrated diagnostic algorithms.
40
Semenov, S. E., E. A. Yurkevich, I. V. Moldavskaia, M. G. Shatokhina, and A. S. Semenov. "DIAGNOSIS OF VENOUS ISCHEMIC STROKE. PART II (ALGORITHMS AND SEMIOLOGY OF DIAGNOSTIC RADIOLOGY. LIMITATIONS IN CLINICAL PRACTICE). A REVIEW." Complex Issues of Cardiovascular Diseases 8, no. 3 (September 26, 2019): 104–15. http://dx.doi.org/10.17802/2306-1278-2019-8-3-104-115.
Full textAbstract:
Venous stroke in cerebral venous sinus thrombosis is a rare pathological condition with uncertain diagnostic algorithm to ensure prompt treatment by neurologists and radiologists. All the methods are not obligatory in the workup of acute stroke, except computed tomography (CT) and transcranial Doppler. Researchers and clinicians are commonly guided by their own experiences. Therefore, the diagnosis of venous stroke is an unstable process resulting in its underestimation in the general stroke population. The optimal use of neuroimaging methods within the existing standards of care for patients with stroke, determination of the necessary and sufficient set of diagnostic procedures is an organizational and methodical problem. In addition, there is no complete description of venous ischemic stroke patterns in the medical literature. The article reviews existing evidence-based data on the diagnostic algorithms for venous stroke and discusses the probability of detecting radiologic symptoms based on the diagnostic accuracy and effectiveness of such methods as conventional CT and magnetic resonance imaging (MRI), CT and MR angiography, CT and MR perfusion, transcranial Doppler (TCD) and ultrasound of the brachiocephalic arteries stated in the national and international guidelines, as well as our own experience. Limitations of their use and options to overcome major drawbacks including the introduction of teleradiology are considered.
41
Sawka, Anna M., Amiram Gafni, Lehana Thabane, and William F. Young. "The Economic Implications of Three Biochemical Screening Algorithms for Pheochromocytoma." Journal of Clinical Endocrinology & Metabolism 89, no. 6 (June 1, 2004): 2859–66. http://dx.doi.org/10.1210/jc.2003-031127.
Full textAbstract:
Abstract Pheochromocytoma is a rare, life-threatening condition. Using a modeling technique, we studied the economic implications of detection strategies for pheochromocytoma (third-party payer perspective). The diagnostic efficacy of biochemical tests was based on Mayo Clinic Rochester data. In all hypothetical algorithms, positive biochemical tests were followed by abdominal computerized tomography and, if negative, metaiodobenzylguanidine scintigraphy. In each hypothetical algorithm, imaging would be indicated after positive biochemical testing as follows: algorithm A, fractionated plasma metanephrine measurements above the laboratory reference range; or algorithm B, abnormal measurements of 24-h urinary total metanephrines or catecholamines. In algorithm C, subjects with fractions of plasma metanephrine at or above 0.5 nmol/liter or normetanephrine at or above 1.80 nmol/liter would undergo imaging, whereas those with values between the reference range and these cutoffs would undergo 24-h urinary measurements (total metanephrines and fractionated catecholamines) and be imaged if positive. We determined that, if 100,000 hypertensive patients (including 500 patients with pheochromocytoma) were tested, algorithm A (measurement of fractionated plasma metanephrines alone) would detect 489 pheochromocytoma patients at a cost of 56.6 million dollars, whereas B (24-h urinary measurements) would detect 457 pheochromocytoma patients for 39.5 million dollars, and C (combination of measurements of fractionated plasma metanephrines and urines) would detect 478 patients for 28.6 million dollars. None of the screening strategies for pheochromocytoma described are affordable if implemented on a routine basis in extremely low-risk patients. However, algorithm C may be the least costly, and at a reasonable level of sensitivity, for subjects in whom the suspicion of disease is moderate.
42
Masood, Ammara, and Adel Ali Al-Jumaily. "Computer Aided Diagnostic Support System for Skin Cancer: A Review of Techniques and Algorithms." International Journal of Biomedical Imaging 2013 (2013): 1–22. http://dx.doi.org/10.1155/2013/323268.
Full textAbstract:
Image-based computer aided diagnosis systems have significant potential for screening and early detection of malignant melanoma. We review the state of the art in these systems and examine current practices, problems, and prospects of image acquisition, pre-processing, segmentation, feature extraction and selection, and classification of dermoscopic images. This paper reports statistics and results from the most important implementations reported to date. We compared the performance of several classifiers specifically developed for skin lesion diagnosis and discussed the corresponding findings. Whenever available, indication of various conditions that affect the technique’s performance is reported. We suggest a framework for comparative assessment of skin cancer diagnostic models and review the results based on these models. The deficiencies in some of the existing studies are highlighted and suggestions for future research are provided.
43
Sodhi, Kushaljit Singh, Niranjan Khandelwal, Akshay Kumar Saxena, Meenu Singh, Ritesh Agarwal, Anmol Bhatia, and Edward Y. Lee. "Rapid lung MRI in children with pulmonary infections: Time to change our diagnostic algorithms." Journal of Magnetic Resonance Imaging 43, no. 5 (November 6, 2015): 1196–206. http://dx.doi.org/10.1002/jmri.25082.
Full text
44
Nair, A., J. C. L. Rodrigues, S. S. Hare, A. Edey, A. Devaraj, J. Jacob, A. Johnstone, R. McStay, E. Denton, and G. Robinson. "A British Society of Thoracic Imaging statement: considerations in designing local imaging diagnostic algorithms for the COVID-19 pandemic. A reply." Clinical Radiology 75, no. 8 (August 2020): 637. http://dx.doi.org/10.1016/j.crad.2020.05.007.
Full text
45
Webers, C., S. Grimm, A. Van Tubergen, F. A. Van Gaalen, D. Van der Heijde, M. Joore, and A. Boonen. "THU0549 COST-EFFECTIVENESS OF DIAGNOSING AXIAL SPONDYLOARTHRITIS IN THE NETHERLANDS." Annals of the Rheumatic Diseases 79, Suppl 1 (June 2020): 514.1–515. http://dx.doi.org/10.1136/annrheumdis-2020-eular.1065.
Full textAbstract:
Background:In order to facilitate diagnosis of axial spondyloarthritis (axSpA) in clinical practice, three diagnostic algorithms have been published: the original Berlin algorithm (BER), and modifications 1 (M1) and 2 (M2). These mainly differed mainly in the position and definition of inflammatory back pain (Figure). BER was the most specific of these algorithms, while M2 was most sensitive, and the latter was accepted as the algorithm of choice. However, it is unknown to what extent it is acceptable, in terms of costs and effects, to increase sensitivity (i.e. reducing underdiagnosis and undertreatment) at the expense of specificity (i.e. increasing overdiagnosis and overtreatment).Figure.Flowchart of the Berlin algorithm (A), and Modifications 1 (B) and 2 (C)Objectives:To compare lifetime cost-effectiveness of currently available diagnostic algorithms for axSpA in the Netherlands.Methods:A cost-effectiveness model was developed to estimate costs, quality adjusted life years (QALYs) and net monetary benefit (NMB) of different diagnostic algorithms for axSpA among patients with chronic low back pain (CLBP) referred to a rheumatologist, over a 60-year time horizon. The model combined a decision-tree (diagnostic process) with a state-transition model (long-term treatment). For the diagnostic process, patient-level data from an observational cohort of referred CLBP patients (SPondyloArthritis Caught Early, SPACE) were used. In the state-transition model, both axSpA and CLBP were modelled using three health states each, based on disease activity and treatment (including up to three sequential biologicals) (for axSpA), or disease severity (for CLBP). Three available diagnostic algorithms (BER, M1, M2) were compared. To estimate the impact of uncertainty on results, probabilistic sensitivity analyses were conducted. For all analyses, both a societal perspective (including all healthcare, informal and work-related costs) and a healthcare perspective (only including healthcare costs) were adopted. Results were expressed as incremental cost-utility ratio (ICUR) and incremental NMB (iNMB).Results:From a societal perspective, algorithm M2 resulted in more QALYs and lowest costs per patient (24.23 QALY; €157,274), thus dominating BER and M1 (Table). From a healthcare perspective, BER had lowest costs, but M2 was still considered cost-effective at €3,250/QALY (Table). At a willingness-to-pay (WTP) threshold of €20,000 per one QALY gained, the probability of M2 being most cost-effective was 94%, compared to 5% for M1 and 1% for BER. Compared to the most cost-effective algorithm (M2), an additional €7,500 could be spent per patient to achieve perfect diagnosis while remaining cost-effective.Table.Base-case deterministic cost-utility results of comparisons between diagnostic algorithmsPerspectiveAlgorithmSE/SPCost, €QALYiCost, €iQALYICUR, €/QALYiNMB, €*SocietalM251% / 88%157,27424.23----M173% / 82%158,23624.15962-0.08Dominated by M2-2,583Berlin80% / 85%159,29523.962,021-0.27Dominated by M2-7,479HealthcareBerlin51% / 88%91,75523.96----M273% / 82%92,64224.238870.273,2504,571M180% / 85%92,71024.1567-0.08Dominated by M2-1,688*Calculated using a WTP threshold of €20,000/QALY. iCost, incremental cost; iQALY, incremental QALY; SE, sensitivity; SP, specificity.Conclusion:The relative increase in sensitivity of M2 at the expense of specificity when compared to the original BER algorithm is acceptable in terms of costs and effects from both societal and healthcare perspectives. A considerably more expensive diagnostic algorithm with better accuracy than M2 would still be considered good value for money. It is worthy to invest in more accurate diagnosis in axSpA.Disclosure of Interests:Casper Webers: None declared, Sabine Grimm: None declared, Astrid van Tubergen Consultant of: Novartis, Floris A. van Gaalen: None declared, Désirée van der Heijde Consultant of: AbbVie, Amgen, Astellas, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Cyxone, Daiichi, Eisai, Eli-Lilly, Galapagos, Gilead Sciences, Inc., Glaxo-Smith-Kline, Janssen, Merck, Novartis, Pfizer, Regeneron, Roche, Sanofi, Takeda, UCB Pharma; Director of Imaging Rheumatology BV, Manuela Joore: None declared, Annelies Boonen Grant/research support from: AbbVie, Consultant of: Galapagos, Lilly (all paid to the department)
46
Eremici, Ivana, Catalin Dumitru, Dan Navolan, Marius Craina, Viviana Ivan, Florin Borcan, Cristina Adriana Dehelean, Ioana Mozos, and Dana Stoian. "Diagnostic Value of Different Risk-Stratification Algorithms in Solid Breast Lesions." Applied Sciences 10, no. 19 (October 4, 2020): 6943. http://dx.doi.org/10.3390/app10196943.
Full textAbstract:
In the past few years, elastography has gained ground as a complementary method to ultrasonography in noninvasive breast cancer screening. Despite positive outcomes, there is a further need to refine the method, especially regarding BIRADS scores 3 and 4A, where the distinction between benignancy and malignancy is established. The aim of the present study was to evaluate the best risk-stratification system using both qualitative and semiquantitative elastographic methods for solid breast nodules. A total of 1405 solid nodules, described in 657 female patients, were examined in our endocrine unit between January 2018 and December 2019. The inclusion criterion for our retrospective study was the presence of any solid breast mass in women of all ages (mean, 40.85 ± SD 27.11), detected during ultrasound examination using a HITACHI PREIRUS machine (Hitachi Medical Corporation, Tokyo, Japan). The Breast Imaging Reporting and Data System (BIRADS)–US criteria were used in the assessment of each nodule by conventional US (gray-scale mode) and Doppler evaluation. The Ueno score and strain ratio were also measured for all the described lesions. We considered multiple algorithms for the risk reassessment of solid breast nodules: classical BIRADS–US, EFSUMB BIRADS, worst-case scenario BIRADS and BIRADS TM. There were 93 malignant nodules out of 1405. The diagnosis was based on histopathological results for all the malignant lesions. Benign lesions were diagnosed based on histopathological results, Tru-Cut biopsy, mammography and MRI. The Sensitivity (Se), Specificity (Sp), Positive Predictive Value (PPV), Negative Predictive Value (NPV) and Accuracy (Acc) were obtained for all the proposed risk-stratification reporting systems: conventional BIRADS-US (Se, 74.23%; Sp, 63.95%; PPV, 13.53%; NPV, 97.79%; Acc, 65%); EFSUMB BIRADS (Se, 71.23%; Sp, 81.55%; PPV, 22.68%; NPV, 97.99%; Acc, 81%); worst-case scenario BIRADS (Se, 84.23%; Sp, 58.23%; PPV, 13.29%; NPV, 98.84%; Acc, 60%); BIRADS TM (Se, 81.23%; Sp, 75.84%; PPV, 20.35%; NPV, 98.81%; Acc, 77%). We found that the most efficient risk-stratification reporting system was the proposed one, BIRADS TM, which considers both upgrading and downgrading the conventional BIRADS-US, followed by the worst-case scenario BIRADS and EFSUMB BIRADS.
47
Inal, Tolga, Gokce Kaan Atac, and Ziya Telatar. "Effect of Noise Adaptive Wavelet Filter on Diagnostic Performance in Stroke Perfusion." Journal of Medical Imaging and Health Informatics 11, no. 3 (March 1, 2021): 720–29. http://dx.doi.org/10.1166/jmihi.2021.3341.
Full textAbstract:
Background: Computed tomography perfusion (CTP) images include more noise than routine clinic computed tomography (CT) images. Singular value decomposition based deconvolution algorithms are widely used for obtaining several functional perfusion maps. Recently block circulant singular value decomposition algorithms become popular for its superior property of immunity to contrast bolus lag. It is well known from literature that these algorithms are very sensitive to noise. There are a lot of examples of noise reduction filters in the literature as well as commercial ones. Functional maps which help physicians in the diagnostic process can be obtained with better image quality by de-noising CTP images with adaptive noise reduction filters. Objective: In this study, the effect of a noise adaptive wavelet filtering method on diagnostic performance on CTP stroke patient images is investigated. Method: Images of acute stroke patients were de-noised by this method and their diagnostic value were evaluated by visual means, peak signal-to-noise ratio and time intensity profile metrics. An observer evaluation study was carried out in order to validate quantitative image quality metrics. The results are compared with Gaussian and a bilateral filter based filtering method called TIPS (Time Intensity Profile Similarity) on same images sets to benchmark proposed method. Results: The diagnostic value of the images obtained from noise adaptive wavelet filtering method were better than Gaussian filter method and were compatible with a wellknown time intensity profile similarity bilateral filter method. Diagnostic performance of the both observers were improved compared to both Gaussian and TIPS methods. Conclusion: The noise adaptive wavelet filter method succeeded to reduce noise while preserving details contained in the contrast bolus. Its final effect on the timeintensity profiles and generated perfusion maps are compatible with the literature and showed improvements on diagnostic performance on specificity and overall accuracy when compared to other methods.
48
Ali Ebrahim, Seham Muawadh. "Hybrid Chaotic Method for Medical Images Ciphering." International Journal of Network Security & Its Applications 12, no. 6 (November 30, 2020): 1–14. http://dx.doi.org/10.5121/ijnsa.2020.12601.
Full textAbstract:
Healthcare is an essential application of e-services, where for diagnostic testing, medical imaging acquiring, processing, analysis, storage, and protection are used. Image ciphering during storage and transmission over the networks used has seen implemented using many types of ciphering algorithms for security purpose. Current cyphering algorithms are classified into two types: traditional classical cryptography using standard algorithms (DES, AES, IDEA, RC5, RSA, ...) and chaos cryptography using continuous (Chau, Rossler, Lorenz, ...) or discreet (Logistics, Henon, ...) algorithms. The traditional algorithms have struggled to combat image data as compared to regular textual data. Whereas, the chaotic algorithms are more efficient for image ciphering. The Significancecharacteristics of chaos are its extreme sensitivity to initial conditions and algorithm parameters. In this paper, medical image security based on hybrid/mixed chaotic algorithms is proposed. The proposed method is implemented using MATLAB. Where the image of the Retina of the Eye to detect Blood Vessels is ciphered. The Pseudo-Random Numbers Generators (PRNGs) from the different chaotic algorithms are implemented, and their statistical properties are evaluated using the National Institute of Standards and Technology NIST and other statistical test-suits. Then, these algorithms are used to secure the data, where the statistical properties of the cipher-text are also tested. We propose two PRNGs to increase the complexity of the PRNGs and to allow many of the NIST statistical tests to be passed: one based on twohybrid mixed chaotic logistic maps and one based on two-hybrid mixed chaotic Henon maps, where each chaotic algorithm runs side-by-side andstarts with random initial conditions and parameters (encryption keys). The resulting hybrid PRNGs passed many of the NIST statistical test suits.
49
Linnemann, Birgit, Rupert Bauersachs, Hannelore Rott, Susan Halimeh, Rainer Zotz, Andrea Gerhardt, Barbara Boddenberg-Pätzold, Bettina Toth, and Ute Scholz. "Diagnosis of pregnancy-associated venous thromboembolism - position paper of the Working Group in Women’s Health of the Society of Thrombosis and Haemostasis (GTH)." Vasa 45, no. 2 (April 2016): 87–101. http://dx.doi.org/10.1024/0301-1526/a000503.
Full textAbstract:
Abstract. Pregnancy and the postpartum period are associated with an increased risk of venous thromboembolism (VTE). Over the past decade, new diagnostic algorithms have been established, combining clinical probability, laboratory testing and imaging studies for the diagnosis of deep vein thrombosis (DVT) and pulmonary embolism (PE) in the non-pregnant population. However, there is no such generally accepted algorithm for the diagnosis of pregnancy-associated VTE. Studies establishing clinical prediction rules have excluded pregnant women, and prediction scores currently in use have not been prospectively validated in pregnancy or during the postpartum period. D-dimers physiologically increase throughout pregnancy and peak at delivery, so a negative D-dimer test result, based on the reference values of non-pregnant subjects, becomes unlikely in the second and third trimesters. Imaging studies therefore play a major role in confirming suspected DVT or PE in pregnant women. Major concerns have been raised against radiologic imaging because of foetal radiation exposure, and doubts about the diagnostic value of ultrasound techniques in attempting to exclude isolated iliac vein thrombosis grow stronger as pregnancy progresses. As members of the Working Group in Women’s Health of the Society of Thrombosis and Haemostasis (GTH), we summarise evidence from the available literature and aim to establish a more uniform strategy for diagnosing pregnancy-associated VTE.
50
Karimova, E. Jane, and Priscilla J. Slanetz. "Charged with Discharge: A Case-based Review of Nipple Discharge Using the American College of Radiology’s Appropriateness Guidelines." Journal of Breast Imaging 2, no. 3 (April 24, 2020): 275–84. http://dx.doi.org/10.1093/jbi/wbaa014.
Full textAbstract:
Abstract Nipple discharge, a relatively common presenting symptom for women of all ages, may be due to both benign and malignant conditions. Men can also present with nipple discharge, and when they do, they have a higher likelihood of malignancy than women. Radiologists vary in their evaluation of patients with nipple discharge, although the American College of Radiology practice guidelines for nipple discharge provides data-driven appropriate algorithms. In patients with physiologic discharge, imaging is not typically indicated. For those with pathologic nipple discharge, imaging typically starts with diagnostic mammography and retroareolar ultrasound for women over 40 years of age, diagnostic mammogram or ultrasound for women aged 30–39 years, and ultrasound for women younger than 30 years. Finally, contrast-enhanced breast MRI or galactography are usually reserved for identifying the cause of discharge when initial imaging with mammography and ultrasound is unrevealing.