Open AccessDeep learning–assisted differentiation of pathologically proven atypical and typical hepatocellular carcinoma (HCC) versus non-HCC on contrast-enhanced MRI of the liver
Author(s) -
Paula M Oestmann,
Clinton J. Wang,
Lynn Jeanette Savic,
Charlie Alexander Hamm,
Sophie Stark,
Isabel Schobert,
Bernhard Gebauer,
Todd Schlachter,
MingDe Lin,
Jeffrey C. Weinreb,
Ramesh Batra,
David Mulligan,
Xuchen Zhang,
James S. Duncan,
Julius Chapiro
Publication year - 2021
Publication title -
european radiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.606
H-Index - 149
eISSN - 1432-1084
pISSN - 0938-7994
DOI - 10.1007/s00330-020-07559-1
Subject(s) - medicine , hepatocellular carcinoma , neuroradiology , grading (engineering) , lesion , radiology , magnetic resonance imaging , receiver operating characteristic , pathology , neurology , civil engineering , psychiatry , engineering
To train a deep learning model to differentiate between pathologically proven hepatocellular carcinoma (HCC) and non-HCC lesions including lesions with atypical imaging features on MRI.