AIMC Journal:
Radiology
Showing 331 to 340 of 374 articles
Prospective Comparison of Standard and Deep Learning-reconstructed Turbo Spin-Echo MRI of the Shoulder.
Radiology
Jan 1, 2024
Background Deep learning (DL)-based MRI reconstructions can reduce imaging times for turbo spin-echo (TSE) examinations. However, studies that prospectively use DL-based reconstructions of rapidly acquired, undersampled MRI in the shoulder are lackin...
Revolutionizing Shoulder MRI: Accelerated Imaging with Deep Learning Reconstruction.
Radiology
Jan 1, 2024
Present and Future Innovations in AI and Cardiac MRI.
Radiology
Jan 1, 2024
Cardiac MRI is used to diagnose and treat patients with a multitude of cardiovascular diseases. Despite the growth of clinical cardiac MRI, complicated image prescriptions and long acquisition protocols limit the specialty and restrain its impact on ...
Comparison of Commercial AI Software Performance for Radiograph Lung Nodule Detection and Bone Age Prediction.
Radiology
Jan 1, 2024
Background Multiple commercial artificial intelligence (AI) products exist for assessing radiographs; however, comparable performance data for these algorithms are limited. Purpose To perform an independent, stand-alone validation of commercially ava...
How AI May Transform Musculoskeletal Imaging.
Radiology
Jan 1, 2024
While musculoskeletal imaging volumes are increasing, there is a relative shortage of subspecialized musculoskeletal radiologists to interpret the studies. Will artificial intelligence (AI) be the solution? For AI to be the solution, the wide impleme...
FDA Review of Radiologic AI Algorithms: Process and Challenges.
Radiology
Jan 1, 2024
A Food and Drug Administration (FDA)-cleared artificial intelligence (AI) algorithm misdiagnosed a finding as an intracranial hemorrhage in a patient, who was finally diagnosed with an ischemic stroke. This scenario highlights a notable failure mode ...
Mammography Breast Cancer Screening Triage Using Deep Learning: A UK Retrospective Study.
Radiology
Nov 1, 2023
Background Breast screening enables early detection of cancers; however, most women have normal mammograms, resulting in repetitive and resource-intensive reading tasks. Purpose To investigate if deep learning (DL) algorithms can be used to triage ma...
Deep Learning Using CT to Improve Chronic Total Occlusion Recanalization Success.
Radiology
Nov 1, 2023
Deep Learning-based Prediction of Percutaneous Recanalization in Chronic Total Occlusion Using Coronary CT Angiography.
Radiology
Nov 1, 2023
UNLABELLED: Background CT is helpful in guiding the revascularization of chronic total occlusion (CTO), but manual prediction scores of percutaneous coronary intervention (PCI) success have challenges. Deep learning (DL) is expected to predict succes...
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