Region-specific deep learning models for accurate segmentation of rectal structures on post-chemoradiation T2w MRI: a multi-institutional, multi-reader study

Region-specific deep learning models for accurate segmentation of rectal structures on post-chemoradiation T2w MRI: a multi-institutional, multi-reader study

IntroductionFor locally advanced rectal cancers, in vivo radiological evaluation of tumor extent and regression after neoadjuvant therapy involves implicit visual identification of rectal structures on magnetic resonance imaging (MRI). Additionally, newer image-based, computational approaches (e.g.,...

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Bibliographic Details
Main Authors: Thomas DeSilvio, Jacob T. Antunes, Kaustav Bera, Prathyush Chirra, Hoa Le, David Liska, Sharon L. Stein, Eric Marderstein, William Hall, Rajmohan Paspulati, Jayakrishna Gollamudi, Andrei S. Purysko, Satish E. Viswanath
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-05-01
Series:Frontiers in Medicine
Subjects:
rectal cancer (RC)
deep learning
MRI
segmentation
U-Net
artificial intelligence (AI)
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2023.1149056/full

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