Deep learning auto-segmentation on multi-sequence magnetic resonance images for upper abdominal organs

Deep learning auto-segmentation on multi-sequence magnetic resonance images for upper abdominal organs

IntroductionMulti-sequence multi-parameter MRIs are often used to define targets and/or organs at risk (OAR) in radiation therapy (RT) planning. Deep learning has so far focused on developing auto-segmentation models based on a single MRI sequence. The purpose of this work is to develop a multi-sequ...

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Bibliographic Details
Main Authors: Asma Amjad, Jiaofeng Xu, Dan Thill, Ying Zhang, Jie Ding, Eric Paulson, William Hall, Beth A. Erickson, X. Allen Li
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-07-01
Series:Frontiers in Oncology
Subjects:
auto-segmentation
multi-sequence MRI
abdominal organs
deep learning
MRI-guided RT
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2023.1209558/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2023.1209558/full

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