Auto-Detection of Motion Artifacts on CT Pulmonary Angiograms with a Physician-Trained AI Algorithm

Auto-Detection of Motion Artifacts on CT Pulmonary Angiograms with a Physician-Trained AI Algorithm

<b>Purpose</b>: Motion-impaired CT images can result in limited or suboptimal diagnostic interpretation (with missed or miscalled lesions) and patient recall. We trained and tested an artificial intelligence (AI) model for identifying substantial motion artifacts on CT pulmonary angiogra...

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Bibliographic Details
Main Authors: Giridhar Dasegowda, Bernardo C. Bizzo, Parisa Kaviani, Lina Karout, Shadi Ebrahimian, Subba R. Digumarthy, Nir Neumark, James M. Hillis, Mannudeep K. Kalra, Keith J. Dreyer
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Diagnostics
Subjects:
artificial intelligence
motion artifact
CT pulmonary angiography
quality improvement
Online Access:https://www.mdpi.com/2075-4418/13/4/778

Internet

https://www.mdpi.com/2075-4418/13/4/778

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