Fully semantic segmentation for rectal cancer based on post-nCRT MRl modality and deep learning framework

Fully semantic segmentation for rectal cancer based on post-nCRT MRl modality and deep learning framework

Abstract Purpose Rectal tumor segmentation on post neoadjuvant chemoradiotherapy (nCRT) magnetic resonance imaging (MRI) has great significance for tumor measurement, radiomics analysis, treatment planning, and operative strategy. In this study, we developed and evaluated segmentation potential excl...

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Bibliographic Details
Main Authors: Shaojun Xia, Qingyang Li, Hai-Tao Zhu, Xiao-Yan Zhang, Yan-Jie Shi, Ding Yang, Jiaqi Wu, Zhen Guan, Qiaoyuan Lu, Xiao-Ting Li, Ying-Shi Sun
Format: Article
Language:English
Published: BMC 2024-03-01
Series:BMC Cancer
Subjects:
Deep learning
Different tumor regression grades
Post-nCRT MRI
Rectal cancer
Semantic segmentation
Online Access:https://doi.org/10.1186/s12885-024-11997-1

Internet

https://doi.org/10.1186/s12885-024-11997-1

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