Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
Sep 1, 2021
OBJECTIVE: To explore the clinical feasibility of applying deep learning (DL) reconstruction algorithm in low-dose thin-slice liver CT examination of healthy volunteers by comparing the reconstruction algorithm based on DL, filtered back projection (...
BACKGROUND: Artificial intelligence (AI) algorithms can be trained to recognise tuberculosis-related abnormalities on chest radiographs. Various AI algorithms are available commercially, yet there is little impartial evidence on how their performance...
OBJECTIVE: This study aimed to conduct objective and subjective comparisons of image quality among abdominal computed tomography (CT) reconstructions with deep learning reconstruction (DLR) algorithms, model-based iterative reconstruction (MBIR), and...
Journal of the American Medical Informatics Association : JAMIA
Jun 12, 2021
BACKGROUND: Artificial intelligence (AI) is increasingly being proposed for use in medicine, including breast cancer screening (BCS). Little is known, however, about referring primary care providers' (PCPs') preferences for this technology.
To evaluate the rib fracture detection performance in computed tomography (CT) images using a software based on a deep convolutional neural network (DCNN) and compare it with the rib fracture diagnostic performance of doctors.We included CT images fr...
Along with recent developments in deep learning techniques, computer-aided diagnosis (CAD) has been growing rapidly in the medical imaging field. In this work, we evaluate the deep learning-based CAD algorithm (DCAD) for detecting and localizing 3 ma...
The aim of this study was to develop an automated segmentation approach for small gross tumor volumes (GTVs) in 3D planning computed tomography (CT) images using dense V-networks (DVNs) that offer more advantages in segmenting smaller structures than...
Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
Mar 1, 2021
OBJECTIVE: To evaluate the noise reduction effect of deep learning-based reconstruction algorithms in thin-section chest CT images by analyzing images reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction (A...
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