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2020 – today
- 2025
[j16]Yabin Shao
, Youlin Hua, Zengtai Gong, Xueqin Zhu, Yunlong Cheng, Laquan Li, Shuyin Xia:
Con-MGSVM: Controllable multi-granularity support vector algorithm for classification and regression. Inf. Fusion 117: 102867 (2025)- [j15]Yonghong Li, Haiyang Qiu, Sidong Xian, Laquan Li, Zhiqiang Zhao, Yang Deng, Jingqing Tang:
Lite-YOLOv8: a more lightweight algorithm for Tubercle Bacilli detection. Medical Biol. Eng. Comput. 63(1): 195-211 (2025) - 2024
- [j14]Xianhua Zeng, Xueyun Nie, Laquan Li, Mingkun Zhou:
Multi-strategy continual learning for knowledge refinement and consolidation. Appl. Intell. 54(20): 10176-10193 (2024) - [j13]Xianhua Zeng, Yongli Guo, Laquan Li, Yuhang Liu:
Continual medical image denoising based on triplet neural networks collaboration. Comput. Biol. Medicine 179: 108914 (2024) - [j12]Laquan Li, Chuangbo Jiang, Lei Yu, Xianhua Zeng, Shenhai Zheng:
Efficient model-informed co-segmentation of tumors on PET/CT driven by clustering and classification information. Comput. Biol. Medicine 180: 108980 (2024) - [j11]Yang Deng, Yonghong Li, Sidong Xian, Laquan Li, Haiyang Qiu:
Mual: enhancing multimodal sentiment analysis with cross-modal attention and difference loss. Int. J. Multim. Inf. Retr. 13(3): 31 (2024) - [c9]Chengcheng Wang, Laquan Li, Dong Qiu:
A Group Decision Making Approach with Z-numbers Based on Choquet Integral. ICMAI 2024: 66-72 - 2023
- [j10]Susu Kang, Zhiyuan Chen, Laquan Li, Wei Lu, X. Sharon Qi, Shan Tan:
Learning feature fusion via an interpretation method for tumor segmentation on PET/CT. Appl. Soft Comput. 148: 110825 (2023) - [j9]Laquan Li, Haiguo Zhao, Hong Wang, Weisheng Li, Shenhai Zheng:
Automatic abdominal segmentation using novel 3D self-adjustable organ aware deep network in CT images. Biomed. Signal Process. Control. 84: 104691 (2023) - [j8]Laquan Li, Chuangbo Jiang, Patrick Shen-Pei Wang, Shenhai Zheng:
3D PET/CT Tumor Co-Segmentation Based on Background Subtraction Hybrid Active Contour Model. Int. J. Pattern Recognit. Artif. Intell. 37(8): 2357006:1-2357006:25 (2023) - [c8]Laquan Li, Yan Jiang:
A Modified Fuzzy Markov Random Field Incorporating Multiple Features for Liver Tumor Segmentation. CICAI (1) 2023: 352-363 - 2022
- [j7]Shixin Huang, Xiaoyu Wan, Hang Qiu, Laquan Li, Haiyan Yu:
Constrained optimization for stratified treatment rules with multiple responses of survival data. Inf. Sci. 596: 343-361 (2022) - [j6]Haosen Liu, Laquan Li, Jiangbo Lu, Shan Tan:
Group Sparsity Mixture Model and Its Application on Image Denoising. IEEE Trans. Image Process. 31: 5677-5690 (2022) - [c7]Shenhai Zheng, Qiuyu Sun, Xin Ye, Weisheng Li, Laquan Li:
Multi-Scale Adversarial Learning and Difficult Supervision for Kidney and Kidney Tumor Segmentation. BMVC 2022: 879 - [c6]Chuangbo Jiang, Shenhai Zheng, Laquan Li:
PET/CT Co-Segmentation Based on Hybrid Active Contour Model. ICIP 2022: 4143-4147 - [c5]Jiaxin Tan, Chuangbo Jiang, Laquan Li, Haoyuan Li, Weisheng Li, Shenhai Zheng:
msFormer: Adaptive Multi-Modality 3D Transformer for Medical Image Segmentation. PRCV (2) 2022: 311-322 - [c4]Shenhai Zheng, Jiaxin Tan, Chuangbo Jiang, Weisheng Li, Laquan Li:
L2-Norm Scaled Transformer for 3D Head and Neck Primary Tumors Segmentation in PET-CT. SMC 2022: 1186-1191 - 2020
- [j5]Shenhai Zheng, Bin Fang, Laquan Li, Mingqi Gao, Yi Wang, Kaiyi Peng:
Automatic liver tumour segmentation in CT combining FCN and NMF-based deformable model. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 8(5): 468-477 (2020) - [j4]Laquan Li, Xiangming Zhao, Wei Lu, Shan Tan:
Deep learning for variational multimodality tumor segmentation in PET/CT. Neurocomputing 392: 277-295 (2020)
2010 – 2019
- 2018
- [j3]Mathieu Hatt, Baptiste Laurent, Anouar Ouahabi, Hadi Fayad, Shan Tan, Laquan Li, Wei Lu, Vincent Jaouen, Clovis Tauber, Jakub Czakon, Filip Drapejkowski, Witold Dyrka, Sorina Camarasu-Pop, Frédéric Cervenansky, Pascal Girard, Tristan Glatard, Michaël Kain, Yao Yao, Christian Barillot, Assen Kirov, Dimitris Visvikis:
The first MICCAI challenge on PET tumor segmentation. Medical Image Anal. 44: 177-195 (2018) - [j2]Shenhai Zheng, Bin Fang, Laquan Li, Mingqi Gao, Rui Chen, Kaiyi Peng:
B-Spline based globally optimal segmentation combining low-level and high-level information. Pattern Recognit. 73: 144-157 (2018) - 2017
- [j1]Laquan Li, Jian Wang, Wei Lu, Shan Tan:
Simultaneous tumor segmentation, image restoration, and blur kernel estimation in PET using multiple regularizations. Comput. Vis. Image Underst. 155: 173-194 (2017) - [c3]Shenhai Zheng, Bin Fang, Laquan Li, Mingqi Gao, Hongsuo Zhang, Hengxin Chen, Yi Wang:
A novel variational method for liver segmentation based on statistical shape model prior and enforced local statistical feature. ISBI 2017: 261-264 - [c2]Shenhai Zheng, Bin Fang, Laquan Li, Mingqi Gao, Yi Wang, Kaiyi Peng:
Automatic Liver Lesion Segmentation in CT Combining Fully Convolutional Networks and Non-negative Matrix Factorization. BIVPCS/POCUS@MICCAI 2017: 44-51 - 2016
- [c1]Shenhai Zheng, Bin Fang, Patrick S. P. Wang, Laquan Li, Mingqi Gao:
Multi-scale B-spline level set segmentation based on Gaussian kernel equalization. ICIP 2016: 4319-4323
Coauthor Index
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