Multi-scale B-spline level set segmentation based on Gaussian kernel equalization. - Shenhai Zheng; Bin Fang 001; Patrick S. P. Wang; Laquan Li; Mingqi Gao 001 (ICIP, 2016)

A novel variational method for liver segmentation based on statistical shape model prior and enforced local statistical feature. - Shenhai Zheng; Bin Fang 001; Laquan Li; Mingqi Gao 001; Hongsuo Zhang; Hengxin Chen; Yi Wang 074 (ISBI, 2017)

Automatic Liver Lesion Segmentation in CT Combining Fully Convolutional Networks and Non-negative Matrix Factorization. - Shenhai Zheng; Bin Fang 001; Laquan Li; Mingqi Gao 001; Yi Wang 074; Kaiyi Peng (BIVPCS/POCUS@MICCAI, 2017)

Simultaneous tumor segmentation, image restoration, and blur kernel estimation in PET using multiple regularizations. - Laquan Li; Jian Wang; Wei Lu 025; Shan Tan (Comput. Vis. Image Underst., 2017)

The first MICCAI challenge on PET tumor segmentation. - Mathieu Hatt; Baptiste Laurent; Anouar Ouahabi; Hadi Fayad; Shan Tan; Laquan Li; Wei Lu 025; Vincent Jaouen; Clovis Tauber; Jakub Czakon; Filip Drapejkowski; Witold Dyrka; et al. (Medical Image Anal., 2018)

B-Spline based globally optimal segmentation combining low-level and high-level information. - Shenhai Zheng; Bin Fang 001; Laquan Li; Mingqi Gao 001; Rui Chen; Kaiyi Peng (Pattern Recognit., 2018)

Automatic liver tumour segmentation in CT combining FCN and NMF-based deformable model. - Shenhai Zheng; Bin Fang 001; Laquan Li; Mingqi Gao 001; Yi Wang 074; Kaiyi Peng (Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2020)

Deep learning for variational multimodality tumor segmentation in PET/CT. - Laquan Li; Xiangming Zhao; Wei Lu 025; Shan Tan (Neurocomputing, 2020)

Multi-Scale Adversarial Learning and Difficult Supervision for Kidney and Kidney Tumor Segmentation. - Shenhai Zheng; Qiuyu Sun; Xin Ye; Weisheng Li 001; Laquan Li (BMVC, 2022)

PET/CT Co-Segmentation Based on Hybrid Active Contour Model. - Chuangbo Jiang; Shenhai Zheng; Laquan Li (ICIP, 2022)

msFormer: Adaptive Multi-Modality 3D Transformer for Medical Image Segmentation. - Jiaxin Tan; Chuangbo Jiang; Laquan Li; Haoyuan Li; Weisheng Li 001; Shenhai Zheng (PRCV (2), 2022)

L2-Norm Scaled Transformer for 3D Head and Neck Primary Tumors Segmentation in PET-CT. - Shenhai Zheng; Jiaxin Tan; Chuangbo Jiang; Weisheng Li 001; Laquan Li (SMC, 2022)

Constrained optimization for stratified treatment rules with multiple responses of survival data. - Shixin Huang; Xiaoyu Wan; Hang Qiu 002; Laquan Li; Haiyan Yu (Inf. Sci., 2022)

Group Sparsity Mixture Model and Its Application on Image Denoising. - Haosen Liu 001; Laquan Li; Jiangbo Lu; Shan Tan (IEEE Trans. Image Process., 2022)

A Modified Fuzzy Markov Random Field Incorporating Multiple Features for Liver Tumor Segmentation. - Laquan Li; Yan Jiang (CICAI (1), 2023)

3D PET/CT Tumor Co-Segmentation Based on Background Subtraction Hybrid Active Contour Model. - Laquan Li; Chuangbo Jiang; Patrick Shen-Pei Wang; Shenhai Zheng (Int. J. Pattern Recognit. Artif. Intell., 2023)

Automatic abdominal segmentation using novel 3D self-adjustable organ aware deep network in CT images. - Laquan Li; Haiguo Zhao; Hong Wang; Weisheng Li 001; Shenhai Zheng (Biomed. Signal Process. Control., 2023)

Learning feature fusion via an interpretation method for tumor segmentation on PET/CT. - Susu Kang; Zhiyuan Chen; Laquan Li; Wei Lu 025; X. Sharon Qi; Shan Tan (Appl. Soft Comput., 2023)

A Group Decision Making Approach with Z-numbers Based on Choquet Integral. - Chengcheng Wang; Laquan Li; Dong Qiu (ICMAI, 2024)

Efficient model-informed co-segmentation of tumors on PET/CT driven by clustering and classification information. - Laquan Li; Chuangbo Jiang; Lei Yu; Xianhua Zeng; Shenhai Zheng (Comput. Biol. Medicine, 2024)

Continual medical image denoising based on triplet neural networks collaboration. - Xianhua Zeng; Yongli Guo; Laquan Li; Yuhang Liu (Comput. Biol. Medicine, 2024)

Mual: enhancing multimodal sentiment analysis with cross-modal attention and difference loss. - Yang Deng; Yonghong Li; Sidong Xian; Laquan Li; Haiyang Qiu (Int. J. Multim. Inf. Retr., 2024)

Multi-strategy continual learning for knowledge refinement and consolidation. - Xianhua Zeng; Xueyun Nie; Laquan Li; Mingkun Zhou (Appl. Intell., 2024)

Federated Hybrid-Supervised Learning for Universal Medical Image Segmentation. - Shenhai Zheng; Sian Wen; Congyu Li; Qing Chen; Laquan Li (ICASSP, 2025)

Con-MGSVM: Controllable multi-granularity support vector algorithm for classification and regression. - Yabin Shao; Youlin Hua; Zengtai Gong; Xueqin Zhu; Yunlong Cheng; Laquan Li; Shuyin Xia (Inf. Fusion, 2025)

Lite-YOLOv8: a more lightweight algorithm for Tubercle Bacilli detection. - Yonghong Li; Haiyang Qiu; Sidong Xian; Laquan Li; Zhiqiang Zhao; Yang Deng; Jingqing Tang (Medical Biol. Eng. Comput., 2025)