Probabilistic minimal path for automated esophagus segmentation
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SPIE
Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. A transformer-guided cross-modality adaptive feature fusion framework for esophageal gross tumor volume segmentation;Computer Methods and Programs in Biomedicine;2024-06
2. Esophageal Tumor Segmentation in CT Images Using a Dilated Dense Attention Unet (DDAUnet);IEEE Access;2021
3. DB M-Net: An Efficient Segmentation Network for Esophagus and Esophageal Tumor in Computed Tomography Images;2020 2nd Symposium on Signal Processing Systems;2020-07-11
4. Eso-Net: A Novel 2.5D Segmentation Network With the Multi-Structure Response Filter for the Cancerous Esophagus;IEEE Access;2020
5. Channel-Attention U-Net: Channel Attention Mechanism for Semantic Segmentation of Esophagus and Esophageal Cancer;IEEE Access;2020
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