MoSID: Modality-Specific Information Disentanglement from Multi-parametric MRI for Breast Tumor Segmentation. - Jiadong Zhang; Qianqian Chen 002; Luping Zhou; Zhiming Cui; Fei Gao 010; Zhenhui Li; Qianjin Feng 003; Dinggang Shen (CaPTion@MICCAI, 2023)

Prompt-Based Segmentation Model of Anatomical Structures and Lesions in CT Images. - Xi Ouyang; Dongdong Gu; Xuejian Li; Wenqi Zhou; Qianqian Chen 002; Yiqiang Zhan; Xiang Sean Zhou; Feng Shi 001; Zhong Xue; Dinggang Shen (MICCAI (8), 2024)

Modality-Specific Information Disentanglement From Multi-Parametric MRI for Breast Tumor Segmentation and Computer-Aided Diagnosis. - Qianqian Chen 002; Jiadong Zhang; Runqi Meng; Lei Zhou 003; Zhenhui Li; Qianjin Feng 003; Dinggang Shen (IEEE Trans. Medical Imaging, 2024)

A Neighbor-Sensitive Multi-Modal Flexible Learning Framework for Improved Prostate Tumor Segmentation in Anisotropic MR Images. - Runqi Meng; Jingli Chen; Kaicong Sun; Qianqian Chen 002; Xiao Zhang 028; Ling Dai; Yuning Gu; Guangyu Wu; Dinggang Shen (IEEE Trans. Biomed. Eng., 2025)