A pilot study using low-dose Spectral CT and ASIR (Adaptive Statistical Iterative Reconstruction) algorithm to diagnose solitary pulmonary nodules. - Huijuan Xiao; Yihe Liu; Hongna Tan; Pan Liang; Bo Wang; Lei Su; Suya Wang; Jianbo Gao (BMC Medical Imaging, 2015)

Multi-level features combined end-to-end learning for automated pathological grading of breast cancer on digital mammograms. - Jinjin Hai; Hongna Tan; Jian Chen 025; Minghui Wu; Kai Qiao; Jingbo Xu 003; Lei Zeng; Fei Gao; Dapeng Shi; Bin Yan 002 (Comput. Medical Imaging Graph., 2019)

Validation of a deep learning mammography model in a population with low screening rates. - Kevin Wu; Eric Wu; Yaping Wu; Hongna Tan; Greg Sorensen; Meiyun Wang; Bill Lotter (CoRR, 2019)

AIDE: Annotation-efficient deep learning for automatic medical image segmentation. - Cheng Li 008; Rongpin Wang; Zaiyi Liu; Meiyun Wang; Hongna Tan; Yaping Wu; Xinfeng Liu; Hui Sun; Rui Yang; Xin Liu 053; Ismail Ben Ayed; Hairong Zheng; et al. (CoRR, 2020)

Whole Mammography Diagnosis via Multi-instance Supervised Discriminative Localization and Classification. - Qingxia Wu; Hongna Tan; Yaping Wu; Pei Dong; Jifei Che; Zheren Li; Chenjin Lei; Dinggang Shen; Zhong Xue; Meiyun Wang (MLMI@MICCAI, 2022)

Cross-view Contrastive Mutual Learning Across Masked Autoencoders for Mammography Diagnosis. - Qingxia Wu; Hongna Tan; Zhi Qiao; Pei Dong; Dinggang Shen; Meiyun Wang; Zhong Xue (MLMI@MICCAI (2), 2023)