目前研究的主要内容包括：
(1) 基于智能计算的医学可视化及三维重构技术及其临床应用
----体绘制可视化技术中三维图像的分类与传递函数设计问题；
----视觉激励的三维图像中隐边界曲面的自适应检测与重构方法研究 (多视觉机制的集成的应用)；
(2) 智能医学影像分析及其临床应用
---- 基于机器学习及先验知识的三维图像中感兴趣器官的分割及体绘制可视化；
---- 计算机辅助的智能医学影像诊断技术及其临床应用（特定类型病灶的检测、分割）
---- 基于机器学习的医学影像中各类异常的自动检测 (计算机该如何学习医生的影像读片能力？)

---- 基于影像组学的医学影像定量分析；基于多组学数据的临床问题定量分析

---- 基于深度学习或影像组学的(智能化及定量化)临床预后分析

(3) 计算机辅助术前手术规划、术中辅助及其临床应用：+3D 打印，+VR

(4) AI及大数据分析在临床诊疗流程中的集成应用：小儿先心病的精准治疗、头颈肿瘤的个性化精准诊疗......

部分论文的目录(*通讯作者，MICCAI及IPMI是领域内的顶会)：
[44] Fuzhen Song, Ruikun Li, Jing Linc, Mingli Lv, Zhaoxia Qian*, Lisheng Wang*, Weibin Wu*,
Predicting the risk of fetal growth restriction by radiomics analysis of the placenta on T2WI: A retrospective case-control study,
Placenta, 134 (2023) 15–22
[43] Ruikun Li, Yujie Guo, Zhongchen Zhao, Mingming Chen, Xiaoqing Liu, Guanzhong Gong*, Lisheng Wang*,
MRI‑based two‑stage deep learning model for automatic detection and segmentation of brain metastases,
European Radiology, 2023, accepted, https://doi.org/10.1007/s00330-023-09420-7
[42] Yuchen Pei, Guocheng Shi, Jieyu Li, Dazhen Sun, Chen Wen, Jiang Li, Meiping Huang, Huiwen Chen*, Lisheng Wang*,
Anatomical attention-based prediction of postoperative pulmonary venous obstruction via CTA images,
Computerized Medical Imaging and Graphics, 103 (2023) 102163
[41] Yuchen Du, Lisheng Wang*, Deyu Meng, Benzhi Chen, Chengyang An, Hao Liu, Weiping Liu, Yupeng Xu, Ying Fan, Dagan Feng, Xiuying Wang, Xun Xu*,
Individualized Statistical Modeling of Lesions in Fundus Images for Anomaly Detection,
IEEE Transactions on Medical Imaging, 2022, accepted, DOI 10.1109/TMI.2022.3225422
[40] Yuchen Pei, Guocheng Shi, Wenjin Xia, Chen Wen, Dazhen Sun, Fang Zhu, ......, Huiwen Chen*, and Lisheng Wang*，
Building a Risk Prediction Model for Postoperative Pulmonary Vein Obstruction via Quantitative Analysis of CTA Images,
IEEE Journal of Biomedical and Health Informatics, 2022, 26(7): 3127-3138
[39] Ningxin Chen, Ruikun Li, Mengmeng Jiang, Yixian Guo, Jiejun Chen, Dazhen Sun, Lisheng Wang*, Xiuzhong Yao*，
Progression-Free Survival Prediction in Small Cell Lung Cancer Based on Radiomics Analysis of Contrast-Enhanced CT，
Frontiers in Medicine，9(2022) 833283
[38] Shuai Liu, Ruikun Li, Qiufang Liu, Dazheng Sun, Hongxing Yang, Herong Pan, Lisheng Wang*, Shaoli Song*,
Radiomics model of 18F-FDG PET/CT imaging for predicting disease-free survival of early-stage uterine cervical squamous cancer,
Cancer Biomarkers 33 (2022) 249–259
[37] Guoqing Bao, Huai Chen, Tongliang Liu, Guanzhong Gong, Yong Yin, Lisheng Wang, and Xiuying Wang,
COVID-MTL: Multitask Learning with Shift3D and Random-weighted Loss for COVID-19 Diagnosis and Severity Assessment,
Pattern Recognition, 124 (2022) 108499
[36] Valentin Oreiller, Vincent Andrearczyk, ......, Lisheng Wang , John O. Prior, Adrien Depeursinge,
Head and neck tumor segmentation in PET/CT: The HECKTOR challenge,
Medical Image Analysis, 77 (2022) 102336
[35] Ruikun Li, Yi-Jie Huang, Huai Chen, Xiaoqing Liu, Yizhou Yu, Dahong Qian, and Lisheng Wang*,
3D Graph-Connectivity Constrained Network for Hepatic Vessel Segmentation,
IEEE Journal of Biomedical and Health Informatics, 26(3): 1251-1262, 2022
[34] Renzhen Wang, Yichen Wu, Huai Chen, Lisheng Wang, and Deyu Meng,
Neighbor Matching for Semi-supervised Learning,
MICCAI2021
[33] Ruchika Verma, Neeraj Kumar, ......, Lata Kini, and Amit Sethi,
MoNuSAC2020: A Multi-organ Nuclei Segmentation and Classification Challenge,
IEEE Transactions on Medical Imaging, 40(12): 3413-3423, 2021
[32] Yuchen Du, Qiuying Chen, Ying Fan, Jianfeng Zhu, ......, David Feng, Michael Fulham, Xiuying Wang, Lisheng Wang* and Xun Xu*,
Automatic identification of Myopic Maculopathy related imaging features in optic disc region via machine learning methods,
Journal of Translational Medicine, 19(167), 2021
[31] Huai Chen, Jiyu Li, RenZhen Wang, Fanrui Meng, Deyu Meng, Qing Peng, Lisheng Wang*,
Unsupervised learning of local discriminative representation for medical images,
IPMI 2021
[30] Jieyu Li, Jayaram K. Udupab, Yubing Tong, Lisheng Wang, Drew A. Torigian,
Segmentation evaluation with sparse ground truth data: Simulating true segmentations as perfect/imperfect as those generated by humans,
Medical Image Analysis, 69 (2021) 101980
[29] Yuxiao Qi, Jieyu Li, Huai Chen, Yujie Guo, Yong Yin, Guanzhong Gong, Lisheng Wang,
Computer‑aided diagnosis and regional segmentation of nasopharyngeal carcinoma based on multi‑modality medical images,
International Journal of Computer Assisted Radiology and Surgery, 16: 871-882, 2021,
[28] Yi-Jie Huang, Qi Dou, Zi-Xian Wang, Li-Zhi Liu, Ying Jin, Chao-Feng Li, Lisheng Wang*, Hao Chen*, Rui-Hua Xu*,
3D RoI-aware U-Net for Accurate and Efficient Colorectal Tumor Segmentation,
IEEE Trans. Cybernetics, 51(11): 5397-5408, 2021
[27] Yibao Li, Shouren Lan, Xin Liu, Bingheng Lu, Lisheng Wang*,
An efficient volume repairing method by using a modified Allen-Cahn equation,
Pattern Recognition, 107 (2020) 107478
[25] Xiyi Wu, Huai Chen, Yijie Huang, Huayan Guo, Tiantian Qiu, Lisheng Wang*,
Center-sensitive and boundary-aware tooth instance segmentation and classification from CBCT,
ISBI 2020
[24] Qiufang Liu, Dazhen Sun, Nan Li, Jinman Kim, Dagan Feng, Gang Huang, Lisheng Wang*, Shaoli Song*,
Predicting EFGR Mutation Subtypes in Lung Adenocarcinoma Using 18F-FDG PET/CT Radiomic Features,
Translational Lung Cancer Research, 2020, 9(3): 549-562
[23] Yi-Jie Huang, Weiping Liu, Xiuying Wang, Qu Fang, Renzhen Wang ,Yi Wang, Huai Chen, Hao Chen, Deyu Meng, Lisheng Wang*,
Rectifying Supporting Regions with Mixed and Active Supervision for Rib Fracture Recognition,
IEEE Transactions on Medical Imaging, 39(12): 3843-383854, 2020
[22] Huai Chen, Yuxiao Qi, Yong Yin, Tengxiang Li, Xiaoqing Liu, Xiuli Li, Guanzhong Gong, Lisheng Wang*,
MMFNet: A Multi-modality MRI Fusion Network for Segmentation of Nasopharyngeal Carcinoma,
Neurocomputing, 394: 27-40, 2020
[21] Benzhi Chen, Lisheng Wang*, Xiuying Wang, Jian Sun, Yijie Huang, Dagan Feng, Zongben Xu,
Abnormality detection in retinal image by individualized background learning,
Pattern Recognition, 2020, 102: 107209,
[20] Jieyu Li, Jayaram K. Udupa, Yubing Tong, Lisheng Wang, Drew A.Torigian,
LinSEM: Linearizing Segmentation Evaluation Metrics for Medical Images,
Medical Image Analysis, 2020, 60: 101601, https://doi.org/10.1016/j.media.2019.101601
[19] Mengmeng Jiang, Dazhen Sun, Yinglong Guo, Yixian Guo, Jie Xiao, Lisheng Wang*, Xiuzhong Yao*,
Assessing PD-L1 Expression Level by Radiomic Features From PET/CT in Nonsmall Cell Lung Cancer Patients: An Initial Result,
Academic Radiology, 27: 171-179, 2020
[18] Renzhen Wang, Benzhi Chen, Deyu Meng, Lisheng Wang
Weakly-Supervised Lesion Detection from Fundus Images,
IEEE Trans. Medical Imaging, 38(6), 1501-1512, 2019.
[17] Huai Chen, Xiuying Wang, Yijie Huang, Xiyi Wu, Yizhou Yu, Lisheng. Wang*,
Harnessing 2D Networks and 3D Features for Automated Pancreas Segmentation from Volumetric CT Images,
MICCAI 2019
[16] Benzhi Chen, Lisheng Wang*, Jian Sun, Huai Chen, Yinghua Fu, Shouren Lan, Yijie Huang, Zongben Xu,
Diverse lesion detection from retinal images by subspace learning over normal samples,
Neurocomputing, 297, 59-70, 2018
[15] Benzhi Chen, Zhihong Fang, Yong Xia, Lan Zhang, Yijie Huang, Lisheng Wang*,
Accurate defect detection via sparsity reconstruction for weld radiographs,
NDT and E International, 94: 62–69, 2018
[14] Heran Yang, Jian Sun, Huibin Li, Lisheng Wang, Zongben Xu
Neural multi-atlas label fusion: Application to cardiac MR images
Medical Image Analysis, 49:60-75, 2018
[13] Shouren Lan, Lisheng Wang*,Yipeng Song, Yu-ping Wang, Liping Yao, Kun Sun, Bin Xia, Zongben Xu,
Improving Separability of Structures with Similar Attributes in 2D Transfer Function Design,
IEEE Trans. Visualization & Computer Graphics, 2017, vol. 23, no. 5, pp. 1546-1560(Regular paper)
[12] Yang Wang, Lin Wu, Huayan Guo, Tiantian Qiu, Yuanliang Huang, Bin Lin and Lisheng Wang*,
Computation of tooth axes of existent and missing teeth from 3D CT images,
Biomedical Engineering-Biomedizinische Technik, vol. 60, no. 6, pp: 623-632, 2015
[11] Shuang Li, Caiwen Xiao, Liyao Duan, Chunlong Fang, Yuanliang Huang, Lisheng Wang*,
CT image-based computer-aided system for orbital prosthesis rehabilitation,
Medical & Biological Engineering & Computing, vol. 53, pp. 943–950, 2015
[10] Lisheng Wang, Pai Wang, Liuhang Cheng, Yu Ma, Shenzhi Wu, Yu-Ping Wang, Zongben Xu,
Detection and reconstruction of an implicit boundary surface by adaptively expanding a small surface patch in a 3D image,
IEEE Trans. Visualization & Computer Graphics, 2014, vol.20, no.11, pp. 1490-1506 (Regular paper)
[9] Lisheng Wang, Zongben Xu,
Quantitative studies on asymptotic growth behaviors of trajectories of nonlinear discrete dynamical systems,
IEEE Trans. Automatic Control, 2014. vol. 59, no.7, pp. 1930-1935
[8] Lisheng Wang, Rui Zhang, Zongben Xu and Jigen Peng,
Some characterizations of global exponential stability of a generic class of continuous-time recurrent neural networks,
IEEE Trans. Systems, Man and Cybernetics-Part B, vol. 39, no.3, pp. 763-772, 2009 (Regular paper)
[7] Lisheng Wang, Jing Bai, Ping He, Pheng-Ann Heng, Xin Yang,
A computational framework for approximating boundary surfaces in 3-D biomedical images,
IEEE Trans. Information Technology in Biomedicine, vol.11, no.6, pp. 668-682, 2007 (Regular paper)
[6] Lisheng Wang, Zongben Xu,
On Characterizations of Exponential Stability of Nonlinear Discrete Dynamical Systems on Bounded Regions,
IEEE Trans. Automatic Control, vol. 52, no. 10, pp. 1871-1881, 2007, (Regular paper)
[5] Lisheng Wang, Zongben Xu, Qunfei Zhao,
Quantitative Characterizations of Exponential Convergence Property of Nonlinear Discrete Dynamical Systems,
IEEE Trans. Automatic Control, vol. 52, no. 11, pp. 2129-2134, 2007
[4] Lisheng Wang, Zongben Xu,
Sufficient and necessary conditions for global exponential stability of discrete-time recurrent neural networks,
IEEE Trans. Circuits & Systems I: Regular paper, vol. 53, no. 6, pp. 1373-1380, 2006 (Regular paper)
[3] Lisheng Wang, Jing Bai, Kui Ying,
Adaptive approximation of the boundary surface of a neuron in confocal microscopy volumetric images,
Medical & Biological Engineering & Computing, vol. 41, no.4, 601-607, 2003
[2] Lisheng Wang, Jing Bai,
Threshold selection by clustering grey levels of boundary,
Pattern Recognition Letters, vol. 24, 1983-1999，2003
[1] Lisheng Wang, Pheng-Ann Heng, Kwong-Sak Leung, Zongben Xu,
Global exponential asymptotic stability in nonlinear discrete dynamical systems,
Journal of Mathematical Analysis & Application, 258(1): 349-358, 2001

参见网页链接： https://automation.sjtu.edu.cn/show/1113

2022年医学影像分析领域顶会MICCAI在2022年举办的三个国际挑战赛

crossMoDA 2022 (Cross-Modality Domain Adaptation for Medical Image Segmentation and Classification)(Task 2)

HECKTOR 2022(Head and neck Tumor segmentation and outcome prediction challenge 2022)(Task 1)

KIPA 2022 (Kidey Parsing for Renal Cancer Treatment 2022 Challenge)
分别以研究生杨涛、孙潇、刘羽晟为首的实验室三个团队参加了上述挑战赛并分别获得 第一名、第二名、第三名。

2021年医学影像分析领域顶会MICCAI在2021年举办的三个国际挑战赛

KiTS2021 (2021 iteration of the Kidney and Kidney Tumor Segmentation Challenge)
FeTA2021(Fetal Brain Tissue Annotation and Segmentation Challenge)
Automatic Segmentation of Head and Neck Primary Tumors in FDG-PET and CT Images
分别以研究生赵忠臣、刘昊、安承洋为首的实验室三个团队参加了上述竞赛，分别 获得第一、第二、第二。

2020年医学影像分析领域顶会MICCAI在2020年举办的两个国际挑战赛
"Thyroid Nodule Segmentation and Classification”，
"Anatomical Brain Barriers to Cancer Spread: Segmentation from CT and MRI images”，
博士生陈怀为首的实验室团队分别参加了上述两个挑战赛，并分别获得 第二名及第三名 。

2020年 医学影像分析领域著名国际会议ISBI在2020年举办的两个国际挑战赛；
“Multi-organ Nuclei Segmentation and Classification”
“Automatic image grading of Diabetic Retinopathy"
分别以硕士生吴希仪、李江为首的实验室两个团队参加了这两个竞赛，均 获得第二名

2019年 医学影像分析领域顶会MICCAI在2019年举办的国际挑战赛
"Automatic Structure Segmentation for Radiotherapy Planning Challenge 2019"；
博士生陈怀为首实验室团队在四项竞赛任务中获得 三项冠军(Tasks 1, 2, 4)及一项第六

竞赛内容：放疗规划中危及器官、靶区的智能勾画, 包括四项不同的智能分割任务：
Task 1: Organ-at-risk segmentation from head & neck CT scans(头颈部危及器官分割)；
Task 2: Gross Target Volume segmentation of nasopharynx cancer(鼻咽癌放疗靶区分割)；
Task 3: Organ-at-risk segmentation from chest CT scans(胸部危及器官(OAR)分割)；
Task 4: Gross Target Volume segmentation of lung cancer(肺癌放疗靶区(GTV)分割)；

2018年南京市人民政府主办全球人工智能大赛，国内外1000多个团队参赛;

2018全球人工智能应用大赛；

博士生陈怀为首的实验室团队参加大赛并获得并列 第三名、二等奖 ；
获奖项目(智能医疗)：“CBCT智能牙根分割”；