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Relevant bibliographies by topics / Low radiation images

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Journal articles

Academic literature on the topic 'Low radiation images'

Author: Grafiati

Published: 23 May 2025

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Journal articles on the topic "Low radiation images"

1

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 (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

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2

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 (2018): 189–97. http://dx.doi.org/10.18280/ama_b.610403.

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3

Woeltjen, Matthias Michael, Julius Henning Niehoff, Arwed Elias Michael, et al. "Low-Dose High-Resolution Photon-Counting CT of the Lung: Radiation Dose and Image Quality in the Clinical Routine." Diagnostics 12, no. 6 (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

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4

Horenko, Illia, Lukáš Pospíšil, Edoardo Vecchi, et al. "Low-Cost Probabilistic 3D Denoising with Applications for Ultra-Low-Radiation Computed Tomography." Journal of Imaging 8, no. 6 (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 denoisi

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5

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 (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

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6

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 (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

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7

Brendlin, Andreas S., David Plajer, Maryanna Chaika, et al. "AI Denoising Significantly Improves Image Quality in Whole-Body Low-Dose Computed Tomography Staging." Diagnostics 12, no. 1 (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 softw

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8

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 (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/pare

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9

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 (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 w

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Zhang, Xinan. "Passive millimeter wave imaging low altitude detection technology." Applied and Computational Engineering 62, no. 1 (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

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