SAUNet++: an automatic segmentation model of COVID-19 lesion from CT slices. - Hanguang Xiao; Zhiqiang Ran; Shingo Mabu; Yuewei Li; Li Li 099 (Vis. Comput., 2023)

MFMANet: Multi-feature Multi-attention Network for efficient subtype classification on non-small cell lung cancer CT images. - Hanguang Xiao; Qiyuan Liu 009; Li Li 099 (Biomed. Signal Process. Control., 2023)

Transformers in medical image segmentation: A review. - Hanguang Xiao; Li Li 099; Qiyuan Liu 009; Xiuhong Zhu; Qihang Zhang (Biomed. Signal Process. Control., 2023)

MSMCNet: Differential context drives accurate localization and edge smoothing of lesions for medical image segmentation. - Ke Peng; Yulin Li; Qingling Xia; Tianqi Liu; Xinyi Shi; Diyou Chen; Li Li 099; Hui Zhao; Hanguang Xiao (Comput. Biol. Medicine, 2023)

Learning high-order spatial interactions and cascaded attention decoding for MRI-based ventricular segmentation. - Hanguang Xiao; Qihang Zhang; Wei Wang; Zhenyu Yi; Shiyi Zhao; Li Li 099 (Biomed. Signal Process. Control., 2024)

UCFilTransNet: Cross-Filtering Transformer-based network for CT image segmentation. - Li Li 099; Qiyuan Liu 009; Xinyi Shi; Yujia Wei; Huanqi Li; Hanguang Xiao (Expert Syst. Appl., 2024)

DFMA-ICH: a deformable mixed-attention model for intracranial hemorrhage lesion segmentation based on deep supervision. - Hanguang Xiao; Xinyi Shi; Qingling Xia; Lihua Chen; Diyou Chen; Yulin Li; Li Li 099; Qiyuan Liu 009; Hui Zhao (Neural Comput. Appl., 2024)

Expert guidance and partially-labeled data collaboration for multi-organ segmentation. - Li Li 099; Jianyi Liu; Hanguang Xiao; Guanqun Zhou; Qiyuan Liu 009; Zhicheng Zhang (Neural Networks, 2025)