Automated detection and delineation of hepatocellular carcinoma on multiphasic contrast-enhanced MRI using deep learning

Purpose Liver Imaging Reporting and Data System (LI-RADS) uses multiphasic contrast-enhanced imaging for hepatocellular carcinoma (HCC) diagnosis. The goal of this feasibility study was to establish a proof-of-principle concept towards automating the application of LI-RADS, using a deep learning alg...

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Veröffentlicht in:	Abdominal imaging 2021-01, Vol.46 (1), p.216-225
Hauptverfasser:	Bousabarah, Khaled, Letzen, Brian, Tefera, Jonathan, Savic, Lynn, Schobert, Isabel, Schlachter, Todd, Staib, Lawrence H., Kocher, Martin, Chapiro, Julius, Lin, MingDe
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial neural networks Automation Carcinoma, Hepatocellular - diagnostic imaging Deep Learning Feasibility studies Gastroenterology Ground truth Hepatocellular carcinoma Hepatology Humans Imaging Lesions Liver Liver cancer Liver Neoplasms - diagnostic imaging Machine learning Magnetic Resonance Imaging Medical imaging Medicine Medicine & Public Health Neural networks Radiology Radiomics Retrospective Studies Segments Technical Test sets Workflow
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