LDNNET: Towards Robust Classification of Lung Nodule and Cancer Using Lung Dense Neural Network. - Ying Chen 023; Yerong Wang; Fei Hu; Longfeng Feng; Taohui Zhou; Cheng Zheng (IEEE Access, 2021)

HADCNet: Automatic segmentation of COVID-19 infection based on a hybrid attention dense connected network with dilated convolution. - Ying Chen; Taohui Zhou; Yi Chen; Longfeng Feng; Cheng Zheng; Lan Liu; Liping Hu; Bujian Pan (Comput. Biol. Medicine, 2022)

Efficient two-step liver and tumour segmentation on abdominal CT via deep learning and a conditional random field. - Ying Chen 023; Cheng Zheng; Fei Hu; Taohui Zhou; Longfeng Feng; Guohui Xu; Zhen Yi; Xiang Zhang (Comput. Biol. Medicine, 2022)

A deep residual attention-based U-Net with a biplane joint method for liver segmentation from CT scans. - Ying Chen 023; Cheng Zheng; Taohui Zhou; Longfeng Feng; Lan Liu; Qiao Zeng; Guoqing Wang (Comput. Biol. Medicine, 2023)

LDANet: Automatic lung parenchyma segmentation from CT images. - Ying Chen; Longfeng Feng; Cheng Zheng; Taohui Zhou; Lan Liu; Pengfei Liu; Yi Chen (Comput. Biol. Medicine, 2023)

BGSNet: A cascaded framework of boundary guided semantic for COVID-19 infection segmentation. - Ying Chen 023; Longfeng Feng; Hongping Lin; Wei Zhang 247; Wang Chen; Zonglai Zhou; Guohui Xu (Biomed. Signal Process. Control., 2024)