OBJECTIVES: This study aimed to validate the agreement and diagnostic performance of a deep-learning-based coronary artery calcium scoring (DL-CACS) system for ECG-gated and non-gated low-dose chest CT (LDCT) across multivendor datasets.
BACKGROUND: To establish the most effective and safe pre-transcatheter aortic valve implantation (TAVI) CT angiography (CTA) protocol by comparing two approaches in terms of image quality, radiation and contrast dose.
Journal of applied clinical medical physics
Sep 1, 2025
PURPOSE: To explore the feasibility of transcatheter aortic valve implantation (TAVI) planning computed tomography (CT) on single-source 8-cm detector scanners with proper dose control by using two deep-learning reconstruction algorithms.
BACKGROUND: Reducing radiation dose from PET imaging is essential to minimize cancer risks; however, it often leads to increased noise and degraded image quality, compromising diagnostic reliability. Recent advances in deep learning have shown promis...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Sep 1, 2025
Low-dose CT (LDCT) significantly reduces the radiation dose received by patients, however, dose reduction introduces additional noise and artifacts. Currently, denoising methods based on convolutional neural networks (CNNs) face limitations in long-r...
The aim of this commentary review was to summarize the main research evidences on radiation exposure and to underline the best clinical and radiological practices to limit radiation exposure in intensive care unit (ICU) patients. Radiological imaging...
OBJECTIVE: To evaluate the impact of deep learning-based image conversion on the accuracy of automated coronary artery calcium quantification using thin-slice, sharp-kernel, non-gated, low-dose chest computed tomography (LDCT) images collected from m...
PURPOSE: This study aimed to investigate the performance of an artificial intelligence (AI)-based lung nodule detection program in ultra-low-dose CT (ULDCT) imaging, with a focus on the influence of various image reconstruction methods on detection a...
In interventional cardiology, occupational radiation exposure for medical personnel can reach high levels, underscoring the critical need for effective radiation protection and monitoring methods. This study employs machine learning algorithms to est...
Low-dose computed tomography (LDCT) denoising plays an important role in medical imaging for reducing the radiation dose to patients. Recently, various data-driven and diffusion-based deep learning (DL) methods have been developed and shown promising...
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