Improved deep learning for automatic localisation and segmentation of rectal cancer on T2‐weighted MRI

Improved deep learning for automatic localisation and segmentation of rectal cancer on T2‐weighted MRI

Abstract Introduction The automatic segmentation approaches of rectal cancer from magnetic resonance imaging (MRI) are very valuable to relieve physicians from heavy workloads and enhance working efficiency. This study aimed to compare the segmentation accuracy of a proposed model with the other thr...

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Bibliographic Details
Main Authors: Zaixian Zhang, Junqi Han, Weina Ji, Henan Lou, Zhiming Li, Yabin Hu, Mingjia Wang, Baozhu Qi, Shunli Liu
Format: Article
Language:English
Published: Wiley 2024-12-01
Series:Journal of Medical Radiation Sciences
Subjects:
Automatic segmentation
convolutional neural network
deep learning
magnetic resonance imaging
rectal cancer
Online Access:https://doi.org/10.1002/jmrs.794
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