Author

Chengwei Chen

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Aug 2026

Dynamic iterative coarse-to-fine prompt learning based on SAM for precise esophageal cancer gross target volume segmentation

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

Aug 2026

Dynamic iterative coarse-to-fine prompt learning based on SAM for precise esophageal cancer gross target volume segmentation

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

#small language model Open access Aug 2026

MGTP-Seg: a mask guidance and text prompting network for gross tumor volume segmentation in esophageal cancer radiotherapy

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