Accurate segmentation of the gross tumor volume from computed tomography images is a core step in the development of precise radiotherapy planning for esophageal cancer, which directly affects treatment efficacy and normal tissue protection. Recently, foundation models represented by the segment anything model (SAM) ha...
Yuxuan Yao, Hong-Fei Sun, Cheng-Wei Chen et al.· Physics in Medicine and Biol...· 0 citations
Background With the widespread application of neoadjuvant immunochemotherapy (nICT) in locally advanced resectable esophageal squamous cell carcinoma (ESCC), determining the optimal postoperative adjuvant treatment strategy has become a critical clinical issue. This study aimed to evaluate the efficacy of different adj...
Xue-Yuan Zhang, Hong-Mei Gao, Jian-Zhong Cao et al.· Frontiers in Immunology· 0 citations
Experimental results show that this segmentation method based on SAM achieves better segmentation performance than existing single-pass methods on both internal and external validation sets, and can provide a reliable efficient scheme for the formulation of precise radiotherapy plans for esophageal cancer.
Yuxuan Yao, Hong-Fei Sun, Cheng-Wei Chen et al.· Physics in Medicine and Biol...· 0 citations
Targeting CTPS1 with STP938, alone or in combination with osimertinib, represents a promising therapeutic strategy and supports CTPS1 as a targetable vulnerability in lung adenocarcinoma.
Hui Xie, Cai-Xia Xu, Bing-Han Zhou et al.· British Journal of Cancer· 0 citations
This work demonstrates that MGTP-Seg not only provides an accurate, interpretable, and clinically relevant solution for automatic GTV delineation, but also offers a novel methodological framework to fuse spatial priors with semantic knowledge in medical image analysis.
Cheng-Wei Chen, Hong-Fei Sun, Yuxuan Yao et al.· Physics in Medicine and Biol...· 0 citations
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