Breast segmentation in MR images using three-dimensional spiral scanning and dynamic programming. - Luan Jiang; Yanyun Lian; Yajia Gu; Qiang Li (Computer-Aided Diagnosis, 2013)

Fully automated segmentation of whole breast in MR images by use of dynamic programming. - Luan Jiang; Yanyun Lian; Yajia Gu; Xiaoxin Hu; Qiang Li (Computer-Aided Diagnosis, 2014)

Fully automated quantitative analysis of breast cancer risk in DCE-MR images. - Luan Jiang; Xiaoxin Hu; Yajia Gu; Qiang Li (Computer-Aided Diagnosis, 2015)

Segmentation of mass in mammograms by a novel integrated active contour method. - Feng Liu; Zhulin Gong; Ying Chen; Yajia Gu (Int. J. Comput. Sci. Eng., 2015)

Application of Image Segmentation and Convolutional Neural Network in Classification Algorithms for Mammary X-ray Molybdenum Target Image. - Minghuan Zhang; Wenjian Liu; Xuan Zhang; Ying Chen; Yajia Gu; Qin Xiao (MICAD, 2020)

Breast Tumor Classification Based on MRI-US Images by Disentangling Modality Features. - Mengyun Qiao; Chencheng Liu; Zeju Li; Jin Zhou; Qin Xiao; Shichong Zhou; Cai Chang; Yajia Gu; Yi Guo 002; Yuanyuan Wang 001 (IEEE J. Biomed. Health Informatics, 2022)

Diagnostic performance characteristics of Chinese radiologists in breast cancer detection with FFDM versus DBT images. - Jia Lin Chua; Qin Xiao; Tong Li; Yajia Gu; Melissa L. Robinson; Kriscia Tapia; Sarah Lewis 001; Phuong Dung Trieu (Image Perception, Observer Performance, and Technology Assessment, 2023)

Domain Generalization for Mammographic Image Analysis via Contrastive Learning. - Zheren Li; Zhiming Cui; Lichi Zhang; Sheng Wang 014; Chenjin Lei; Xi Ouyang; Dongdong Chen 003; Zixu Zhuang; Xiangyu Zhao 003; Yajia Gu; Zaiyi Liu; Chunling Liu; et al. (CoRR, 2023)

Development and validation of peritumoral vascular and intratumoral radiomics to predict pathologic complete responses to neoadjuvant chemotherapy in patients with triple-negative breast cancer. - Tianwen Xie; Jing Gong; Qiufeng Zhao; Chengyue Wu; Siyu Wu; Weijun Peng; Yajia Gu (BMC Medical Imaging, 2024)

Domain generalization for mammographic image analysis with contrastive learning. - Zheren Li; Zhiming Cui; Lichi Zhang; Sheng Wang 014; Chenjin Lei; Xi Ouyang; Dongdong Chen 003; Xiangyu Zhao 003; Chunling Liu; Zaiyi Liu; Yajia Gu; Dinggang Shen; et al. (Comput. Biol. Medicine, 2025)

Multitask deep learning model based on multimodal data for predicting prognosis of rectal cancer: a multicenter retrospective study. - Qiong Ma; Runqi Meng; Ruiting Li; Ling Dai; Fu Shen; Jie Yuan; Danqi Sun; Manman Li; Caixia Fu; Rong Li; Feng Feng; Yonggang Li; et al. (BMC Medical Informatics Decis. Mak., 2025)