Open AccessAutomated knee cartilage segmentation for heterogeneous clinical MRI using generative adversarial networks with transfer learning
Author(s) -
Mingrui Yang,
Ceylan Çolak,
Kishore K. Chundru,
Sibaji Gaj,
Andreas K. Nanavati,
Morgan H. Jones,
Carl S. Winalski,
Naveen Subhas,
Xiaojuan Li
Publication year - 2022
Publication title -
quantitative imaging in medicine and surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.766
H-Index - 21
eISSN - 2223-4306
pISSN - 2223-4292
DOI - 10.21037/qims-21-459
Subject(s) - hausdorff distance , artificial intelligence , computer science , percentile , sørensen–dice coefficient , segmentation , transfer of learning , pattern recognition (psychology) , cross validation , deep learning , machine learning , image segmentation , mathematics , statistics
This study aimed to build a deep learning model to automatically segment heterogeneous clinical MRI scans by optimizing a pre-trained model built from a homogeneous research dataset with transfer learning.
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