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

Purpose: 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 angiography (CTPA) that hav...

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Detalles Bibliográficos
Autores principales: Dasegowda, Giridhar, Bizzo, Bernardo C., Kaviani, Parisa, Karout, Lina, Ebrahimian, Shadi, Digumarthy, Subba R., Neumark, Nir, Hillis, James M., Kalra, Mannudeep K., Dreyer, Keith J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955317/
https://www.ncbi.nlm.nih.gov/pubmed/36832266
http://dx.doi.org/10.3390/diagnostics13040778

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955317/
https://www.ncbi.nlm.nih.gov/pubmed/36832266
http://dx.doi.org/10.3390/diagnostics13040778

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