Accurate and Feasible Deep Learning Based Semi-Automatic Segmentation in CT for Radiomics Analysis in Pancreatic Neuroendocrine Neoplasms. - Bingsheng Huang; Xiaoyi Lin; Jingxian Shen; Xin Chen 025; Jia Chen; Zi-Ping Li; Mingyu Wang; Chenglang Yuan; Xian-Fen Diao; Yanji Luo; Shi-Ting Feng (IEEE J. Biomed. Health Informatics, 2021)

Deep Semantic Segmentation Feature-Based Radiomics for the Classification Tasks in Medical Image Analysis. - Bingsheng Huang; Junru Tian; Hongyuan Zhang 002; Zixin Luo; Jing Qin 001; Chen Huang; Xueping He; Yanji Luo; Yongjin Zhou 002; Guo Dan; Hanwei Chen; Shi-Ting Feng; et al. (IEEE J. Biomed. Health Informatics, 2021)

Integrating with Segmentation by Using Multi-Task Learning Improves Classification Performance in Medical Image Analysis. - Yi Li; Yuanyuan Zhao; Mingyu Wang; Fei Li; Jia Chen; Yanji Luo; Shi-Ting Feng; Xiaoyi Lin; Bingsheng Huang (CBMS, 2022)

Self-feedback Transformer: A Multi-label Diagnostic Model for Real-World Pancreatic Neuroendocrine Neoplasms Data. - Mingyu Wang; Yi Li; Bin Huang; Chenglang Yuan; Yangdi Wang; Yanji Luo; Bingsheng Huang (MICCAI (7), 2023)

Improving Tumor Classification by Reusing Self-Predicted Segmentation of Medical Images as Guiding Knowledge. - Xiaoyi Lin; Mingyu Wang; Fei Li; Ziyue Xu 001; Jia Chen; Xin Chen 025; Chenglang Yuan; Songxiong Wu; Yanji Luo; Jingxian Shen; Shi-Ting Feng; Bingsheng Huang (IEEE J. Biomed. Health Informatics, 2024)