Professor Department of Computer Science and Engineering   Research Group

Jimmy Liu graduated from the Department of Computer Science of the University of Science and Technology of China in 1988. He further obtained his master and doctoral degrees in Computer Science from the National University of Singapore. In 2007, he started the Intelligent Medical Imaging Research Team (iMED Singapore, A*STAR) and grew it to become one of the world's largest ophthalmic medical image processing team, focusing on ophthalmic Artificial Intelligence research. Jimmy was the chairman of the IEEE Singapore Biomedical Engineering Society in Singapore.

In March 2016, Jimmy returned to China and founded the iMED China (Ningbo) team. He was the founding director and senior professor of the Cixi Institute of Biomedical Engineering (CIBE) of the Chinese Academy of Sciences.

In February 2019, he joined the Department of Computer Science and Engineering of the Southern University of Science and Technology to establish iMED China(Shenzhe). .He will devote his time to more fundamental eye-brain, Artificial Intelligence, precision medicine, surgical robotics research.

Personal Profile

Jimmy LIU, Prof.

Email:liuj_AT_sustech.edu.cn
Office:Room 403,Building 10 Innovation Park
Research Area: Ocular (eye) Imaging Artificial Intelligence;Eye-Brain; Medical imaging analysis;Precise Medical;Surgical robots

Educational Background

◆ 1999/05-2004/04, National University of Singapore, computer science department, PhD
◆ 1991/02-1992/11, National University of Singapore, Computer science department, M.S.
◆ 1983/08-1988/07, University of Science and Technology of China, Computer science department, B.S.

 

Professional Experience

◆ 2019/02-NOW,Department of Computer Science and Engineering, Southern University of Science and Technology,Professor
◆ 2016/03-2019/01,Cixi institute of Biomedical Engineering of CAS,Director/Senior Professor
◆ 2007/01-2016/03,Intelligent Medical Imaging Department,Institute of infocomm research, A*STAR, Senior Scientist/Director/Director consultant
◆ 2004/07-2006/12,National University of Singapore,School of Computing,Research Fellow
◆ 1989/09-2004/06,Singapore state-owned/multinational corporation,Engineer/Manager/Technical Director
◆ 1988/09-1989/08,Institute of Automation, Chinese Academy of Sciences,Assistant Engineer

 

Honors & Awards

◆ National Distinguished Scholar
◆ Chief Scientist, National Eye Research Center, Singapore (Adjunct)
◆ IES Prestigious Engineering Achievement, Singapore,2013
◆ ASEAN Graphical System Design Achievement,Singapore,2011

 

Selected Publication

  1. Fei Li, Hao Li, Jianlong Yang, Jiang Liu, Aung Tin, Xiulan Zhang. Upside-down position leads to choroidal expansion and anterior chamber shallowing: OCT study[J]. British Journal of Ophthalmology, 2019: bjophthalmol-2019-314418.
  2. Yifan Zhao ; Yitian Zhao ; Pholpat Durongbhan ; Liangyu Chen ; Jiang Liu ; S. A. Billings ; Panagiotis Zis;Zoe C. Unwin;Matteo De Marco;Annalena Venneri. Imaging of nonlinear and dynamic functional brain connectivity based on EEG recordings with the application on the diagnosis of Alzheimer’s disease[J]. IEEE Transactions on Medical Imaging, 2019.
  3. Lei Mou, Li Chen, Jun Cheng, Zaiwang Gu, Yitian Zhao and Jiang Liu. Dense Dilated Network with Probability Regularized Walk for Vessel Detection[J]. IEEE Transactions on Medical Imaging, 2019.
  4. Zaiwang Gu, Jun Cheng , Huazhu Fu , Kang Zhou, Huaying Hao, Yitian Zhao , Tianyang Zhang, Shenghua Gao , and Jiang Li. CE-Net: Context Encoder Network for 2D Medical Image Segmentation[J]. IEEE Transactions on Medical Imaging, 2019.
  5. Yitian Zhao, Jianyang Xie, Huaizhong Zhang, Yalin Zheng, Yifan Zhao, Hong Qi, Yangchun Zhao, Pan Su∗, Jiang Liu and Yonghuai Liu. Retinal vascular network topology reconstruction and artery/vein classification via dominant set clustering[J]. IEEE Transactions on Medical Imaging, 2019.
  6. Tianyang Zhang, Jun Cheng, Huazhu Fu, Zaiwang Gu, Yuting Xiao, Kang Zhou, Shenghua Gao, Rui Zheng and Jiang Liu. Noise Adaptation Generative Adversarial Network for Medical Image Analysis[J]. IEEE Transactions on Medical Imaging, 2019.
  7. Huazhu Fu, Yanwu Xu, Stephen Lin, Damon Wing Kee Wong, Mani Baskaran, Meenakshi Mahesh, Tin Aung and Jiang Liu. Angle-Closure Detection in Anterior Segment OCT based on Multi-Level Deep Network[J]. IEEE Transactions on Cybernetics,2019
  8. Jianyang Xie, Yitian Zhao, Yonghuai Liu, Pan Su, Yifan Zhao,Jun Cheng, Yalin Zheng, Jiang Liu. Topology Reconstruction of Tree-Like Structure in Images via Structural Similarity Measure and Dominant Set Clustering[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2019: 8505-8513.
  9. Tianyang Zhang, Huazhu Fu, Yitian Zhao, Jun Cheng, Mengjie Guo, Zaiwang Gu, Bing Yang, Yuting Xiao, Shenghua Gao, and Jiang Liu. SkrGAN: Sketching-rendering Unconditional Generative Adversarial Networks for Medical Image Synthesis[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Cham, 2019: 777-785.
  10. Pan Su, Yitian Zhao, Tianhua Chen, Jianyang Xie, Yifan Zhao, Hong Qi, Yalin Zheng, and Jiang Liu. Exploiting Reliability-Guided Aggregation for the Assessment of Curvilinear Structure Tortuosity[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Cham, 2019: 12-20.
  11. Lei Mou, Yitian Zhao, Li Chen, Jun Cheng, Zaiwang Gu, Huaying Hao, Hong Qi , Yalin Zheng, Alejandro Frangi, and Jiang Liu. CS-Net: Channel and Spatial Attention Network for Curvilinear Structure Segmentation[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Cham, 2019: 721-730.
  12. Huazhu Fu,Boyang Wang,Jianbing Shen,Shanshan Cui,Yanwu Xu,Jiang Liu,Ling Shao. Evaluation of retinal image quality assessment networks in different color-spaces[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Cham, 2019: 48-56.
  13. Yitian Zhao, Yalin Zheng, Yonghuai Liu, Yifan Zhao, Lingling Luo, Siyuan Yang, Tong Na, Yongtian Wang, Jiang Liu, Automatic 2D/3D Vessel Enhancement in Multiple Modality Images Using a Weighted Symmetry Filter, IEEE Transactions on Medical Imaging, 37(2): 438-450, 2018
  14. Fu, Jun Cheng, Y. Xu, D. W. K. Wong, J. Liu and X. Cao, Joint Optic Disc and Cup Segmentation Based on Multi-label Deep Network and Polar Transformation, IEEE Transactions on Medical Imaging, vol. 37, no 7, pp. 1597-1605, 2018.
  15. Fu, Jun Cheng, Y. Xu, C. Zhang, D. W. K.Wong, J. Liu, X. Cao, "Disc-aware Ensemble Network for Glaucoma Screening from Fundus Image", IEEE Transactions on Medical Imaging, vol. 37, no. 11, pp. 2493-2501, 2018 .
  16. Jun Cheng, Z. Li, Z. Gu, H. Fu, D. W. K. Wong, J. Liu,"Structure-preserving Guided Retinal Image Filtering and Its Application for Optic Disc Analysis", IEEE Transactions on Medical Imaging, vol. 37, no. 11, pp. 2536-2546, 2018.
  17. Yitian Zhao, Yalin Zheng, Zhili Chen, Peng Liu, Yifan Zhao, Jiang Liu, Uniqueness-Driven Saliency Analysis For Automated Abnormalities Detection with Application to Retinal Diseases, Proceedings of International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 109-118, Granada, Spain, September, 2018.
  18. Yitian Zhao, JianyangXie, Yalin Zheng, Yonghuai Liu, Pan Su, Yifan Zhao, Jun Cheng, Jiang Liu, Retinal Artery and Vein Classification via Dominant Sets Clustering-based Vascular Topology Estimation, Proceedings of International Conference on Medical Image Computing and Computer-Assisted Intervention pp. 56-64, Granada, Spain, September, 2018
  19. Huazhu Fu, Yanwu Xu, Stephen Lin, Damon Wing Kee Wong, Baskaran Mani, Meenakshi Mahesh, Tin Aung, Jiang Liu, "Multi-Context Deep Network for Angle-Closure Glaucoma Screening in Anterior Segment OCT", Proceedings of International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 356-363, 2018
  20. Yifan Zhao, Ramon Laguna, Yitian Zhao, John Yianni, PtolemaiosSarrigiannis, Jimmy Liu Jiang and Xiong-xiong He, A wavelet-based correlation analysis framework to study cerebro-muscular activity in essential tremor, Complexity, 7269494, 2018.

Research

人工智能:开发基于医学图像/眼科影像的自动人工智能疾病诊断算法及技术,实现自动化低成本高精准度眼科疾病筛查

精准医疗:通过与国内外医院广泛合作,收集病人基因及医学图像数据,开发基于人体基因、医学图像和大数据处理的精准医疗算法及技术

眼脑联动:结合眼图像及信号与脑图像及信号,对眼部或脑部进行刺激和反馈,实现对眼疾病和脑疾病的诊断及干预(例如青光眼与阿尔兹海默病)

手术机器人:开发基于医学图像/眼科影像和医疗机器人的自动医学手术引导,辅助算法及技术


Teaching

Introduction To AI

This course provides an introduction to artificial intelligence (AI). Topics talked will help students to achieve the following 3 main objectives:

1) Highlight fundamental AI concepts: including agent, knowledge, search, game theory, reasoning, planning, learning, and importantly biological and psychological foundations behind AI development.

2) Introduce the current data driven deep learning AI models, algorithms and platforms: including the development of deep neural network and various popular deep learning network structures and development platforms.

3) Inspire student’s interest in AI: In order to encourage students to engage AI in their future careers and study, various AI applications will be introduced and discussed. Students are asked to work on AI application projects, group project presentation will be graded.

CS330. Multimedia Information Processing

Lecture, 2 hours per week. Experiment, 2 hours per week, total of 64 hours,3 credits,. Pre-requesites: Computer Science and Technology and Intelligent Science and Technology. This course introduces the concepts, issues, design, implementation, standards and applications of multimedia technologies. The media to be considered include text, digital audio, digital image, digital video, and their integration. The course covers basics and applications of analog and digital media. It discusses the characteristics, mathematical foundation, compression and processing of digital multimedia data including: audio, image (JPEG) and video (MPEG). It also covers standards in digital multimedia data such as MP3, JPEG, MPEG as well as the environment in which digital multimedia data are used, including multimedia architecture, indexing and retrieval, hypermedia and WWW.


Publications Read More

刘江主持过总值超过1亿2千万元的20余项新加坡和中国科研项目,在IEEE-TMI、JIAMA、CVPR、MICCAI等行业顶级国际期刊和会议发表280余篇,申请了50多项国际和国内专利,国际企业专利授权十余项。连续10年刷新基于杯盘比的青光眼人工制智能诊断世界纪录。

News More

  • “团结、专注、坚持”——iMed团队文化

    2020年初春,在全国新冠病毒疫情防控形式严峻的情况下,IMED团队虽然历经了很多前所未有的挑战,最后还是顺利通过了考验。大家在克服困难坚持科研工作的同时,合力完成了国自然和深圳市科创委两项新冠病毒防治项目的申报工作,每个人都功不可没。 继刘江老师年前提出“团结、专注、坚持”为主旨的IMED团队文化,并抛出用三棱镜色散原理实现具象表达的想法,刘慧颖老师第一时间展示了第一稿设计,并赢得了大家的一致赞扬。3月社会秩序陆续恢复常态,IMED团队文化即将定稿印刷。IMED深圳团队助理毕阿璇把第一稿设计整理成矢量图像后,又汇总了团队成员的意见,并结合了自己对团队文化的理解,经过两稿的修改之后,最终定稿。 IMED团队文化,以 “眼科影像”为团队研究核心,IMED所有成员为团队基础,“团结、专注、坚持”六个字为团队发展主旨。希望在2020年这个不平凡的年度,以全新的气息和姿态登场,照亮IMED更辉煌的远方。 作者:毕阿璇

    2020-03-27
  • 通用光学相干层析成像(OCT)和OCT血流造影(OCTA)图像噪声去除方法

    OCT是一种重要的眼科成像模态,具有非侵入式三维成像的特点,已经成为糖尿病视网膜病变、老年性黄斑病变等最常见眼底病的常规检测手段。OCTA是新兴的OCT功能成像,无需注射造影剂便可获得毛细血管形态、灌注以及血流动力学信息。近年来,OCTA已经被大量应用于眼科疾病的研究中,在检测灵敏度、准确性等方面具有显著优势,应用前景非常广阔。      然而,OCT图像中的散斑噪声与OCTA图像中的运动噪声,严重妨碍了眼底组织和血管结构的可视化,并导致难以进行定量分析。针对这一问题,已经大量的研究工作尝试去除OCT和OCTA图像中的噪声。但现有的研究都只针对其中一种有较好的效果。如下图所示,目前最为有效的OCT去噪算法BM4D和K-SVD对OCT图像效果较好,但分别会导致OCTA中毛细血管信息的丢失和模糊。     针对这一现状,近日,医学影像事业部(iMED中国团队)开发出一种能够通用于OCT和OCTA图像去噪的方法,并在两种类型图像的去噪中都取得了超越现有方法的成绩。该方法考虑到OCTA图像中的眼底血管在B扫描中与噪声形态接近,很容易与之混淆。因此提出在三维空间进行去噪,通过利用在en face平面上血管的线状结构特征与噪声相区分。该方法进一步利用到OCT和OCTA信号的稀疏性,采用三维剪切波(shearlet)进行特征变换和分解,并对噪声进行滤波,方法流程如下图所示。     由于剪切波相较于小波(wavelet)、曲线波(curvelet)等具有更强现状特征和边缘特征表示能力,该方法对于散斑噪声和运动噪声同时具有很强的消除能力。此外,由于该方法的无监督(unsupervised)特性,因此对于不同特征(正常、病灶)和不同来源的数据具有很好的鲁棒性和泛化能力。下图是针对一个老年性黄斑病变数据的OCT和OCTA去噪示例。     该项研究成果“Universal digital filtering for denoising volumetric retinal OCT and OCT angiography in 3D shearlet domain”已于2020年2月1日发表在领域权威期刊Optics Letters上(Opt. Lett. 45, 694-697 (2020) https://doi.org/10.1364/OL.383701)。   来自:http://www.imed-lab.com/?p=19469

    2020-03-23
  • 不畏疫情,团结一致,顽强拼搏,打造一支敢想、敢做、勇于亮剑的新团队

    作者:王浩、岳星宇 2020年新年伊始,新冠病毒从武汉席卷全国,疫情变化时时刻刻都牵动着亿万中华儿女的心。每一位中国人都积极参与到了这场疫情防御的人民战争中去。在中国共产党的坚强领导下,我们必将战胜这场没有硝烟的战争。尽管现在疫情还没有结束,但是已接近尾声,各行各业陆续开工、开学。而iMED队员们也陆陆续续回到自己的工作岗位和学习状态。 iMED团队作为一个医学与人工智能交叉的一流研究团队,我们在iMED团队负责人刘江教授的带领下,用我们科研人员独有的方式投身于这场疫情阻击战中。回顾这一个多月,尽管疫情肆虐,我们响应国家号召,利用网络条件,实施远程调用服务器、网络办公和会议、远程课堂等方式,几乎每一位iMED团队成员都时刻对自己的科研和学业毫不松懈。最终交出了一副满意的答卷。 2019年中国农历的最后一天,万家灯火,喜气洋洋,大家都沉浸在新年的喜悦气氛中。就在此时,一场可怕的瘟疫正悄然席卷中华大地。中国基金委认识到这一突发情况,迅速布置了相关领域的科研专项布局。我们iMED团队拥有多年眼科人工智能分析的经验,同国内著名眼科医生一起,第一时间意识到,冠状病毒有可能是通过眼睛传播,同时会对眼部结构功能影像学产生影响。接下来的有关报道也进一步验证了这一观点。于是我们迅速布局,开展了相关项目申请工作。我们邀请了深圳市唯一一家新冠肺炎收治单位,深圳市第三人民医院即南科大第二附属医院,一同参与到此项目中去。深圳市第三人民医院拥有深厚的病毒研究经验,近5年来,医院先后承担国家重大科技专项25项,国家、省自然科学基金36项,累计获得科研经费超过4亿元。发表论文380余篇,包括国际顶尖杂志《N Engl J Med.》、《Science》、《Nature》、《Lancet》等。从项目策划,到项目书撰写,到各种材料的收集,我们有条不紊的进行。短短的几天时间,在iMED全体成员的积极努力和配合下,我们顺利完成了整个项目书和相关附件材料,第一时间提交给了中国基金委。值得一提的是,我们是南科大仅有的四个申报病毒专项的团队之一,并且得到了中国科学院院士陈十一校长的大力赞扬。此次项目申请,充分证明了我们iMED是一个敢想、敢做、勇于创新和亮剑的团队。 同时,深圳市基金委也紧急发起了新冠病毒专项。病毒具有潜伏期长、传播快、致死率高的特点,严重影响人类的生命健康。因此通过便捷有效方式,对易感人群实现远程早期筛查是控制和治疗此次肺炎疫情关键。据传染学专家指出,该病毒感染后,其首发症状在眼部。研究表明冠状病毒感染后可发生从轻度到重度的眼部疾病。通过便捷智能手机和眼科设备拍摄的眼部图像进行智能算法自动分析,是潜在实现该病毒筛查和早期诊断的重要途径,为患者争取关键干预和治疗时间。我们意识到做好通过眼科感染的新冠病毒精准筛查,不仅仅需要眼科图像信息,而且还需要基因信息。于是,我们乘胜追击,联合深圳市第三人民医院、深圳市华大生命研究院和深圳市人民医院眼科一同申报了此次专项。深圳市华大生命研究院致力于生命科学、生物技术和医疗应用领域的多组学研发的非营利机构,在新一代测序技术平台的基因检测产品开发和遗传病致病基因发现及机制研究具有卓越的成绩。深圳市人民医院眼科科室拥有世界一流的眼科设备和眼科诊疗技术。该项在iMED全体成员的积极推动下,已经基本完成项目申报工作。 iMED团队是一个专注于眼科人工智能分析的一流团队,在疫情期间,团队重新确立了“团结、专注、坚持”的团队精神和象征这一精神的logo。同时,团队也重新调整了战略部署、管理架构和团队核心方向。团队确定了以刘江教授为首的管理委员会。在明确了赵一天对于iMED宁波的领导基础上,团队也重新确立了五大研究方向:以赵一天为首的“眼脑联动”方向、以杨建龙为首的眼科智能硬件方向、以胡衍为首的手术导航团队、以RISA为首的眼前节分析团队和以方建生为首的工程团队。他们各司其职,分别领导着包括工程师、博士生、硕士生、本科生在内的十余人的小团队。 在抗击疫情的岁月里,我们iMED团队传承相互关爱的优良传统,发生了许多令人感动的故事。与我们拥有多年合作关系的日本TOMEY集团的RISA博士为我们从日本寄来了100副外科口罩;阿璇为了保障项目申报的顺利进行大年初四从老家安徽赶回了深圳;胡衍加班加点通宵写项目申请书;愿愿冒着被感染的风险去材料所盖章。这一幕幕都戳动了我们的心房,我们为她们点赞和喝彩。 秉承着停课不停学的教育部指示,刘江教授积极备课,通过网络为本科生上《多媒体分析》的课程;赵一天申报了2020年度国际伙伴计划对外合作重点项目;杨燕鹤解决了C-SCAN和B-SCAN的显示问题;星宇和姗姗制定了iMED防疫准则;方建生、胡衍和章晓庆都分别提交了相应的专利和论文等等,还有很多很多,每个iMED成员都做出了自己的贡献。 如果说每个人是一滴水,那我们团队就是一条河。我们只有借助团队的力量、发挥自己的优势,才能惊涛拍浪,撑起万吨巨轮,一路高歌奔向大海。疫情再深,没有我们相互关心的温情深;疫情再高,没有我们团结一致的齐心高;疫情再猛,没有我们顽强拼搏的精神猛。不畏疫情,团结一致,顽强拼搏,打造一支敢想、敢做、勇于亮剑的新团队。 2020年2月23日 于深圳集悦城

    2020-02-24

Lab members Read More

Join us

招聘博士生/博士后/研究助理教授

南方科技大学智能医学影像团队——iMED中国(深圳)是由国家“千人计划”专家刘江教授领导的专注于眼科医学人工智能的科研团队。团队拥有独家的医疗大数据资源,充足的科研经费,同国际国内著名医院及设备厂家深入合作,是一支国际领先的医疗人工智能团队。

由于行业的快速发展及不断更新,希望加入团队的人员有以下3点特质:

(1)喜爱医学人工智能及医疗行业,希望在此行业长期发展;

(2)有强烈的团队精神,对团队内成员谦虚谦让,对团队外合作伙伴真诚尊重;

(3)有持续的学习能力(包括对交叉相关学科包括医学知识的学习能力)。

1、研究方向

1,基于眼科图像的人工智能研究

2,基于眼脑多模态图像眼脑联动疾病诊断研究

3,基于基因/病理/图像联合分析的精准医疗研究

4,基于医学影像的辅助手术机器人研究

2、招聘人数

(1)硕士或博士研究生若干

(2)博士后:4名

(3)研究助理教授:4名

3、招聘条件

(1)具有理学/工学/医学博士学位(研究生招生除外);

(2)工作严谨、主动,具备高度的工作责任心和良好的团队精神及职业素养;

(3)良好的科研背景和经验,高质量文章发表记录;

满足以下条件之一优先:

(4)有Python/MATLAB等编程经验,可以从事计算机图像处理机器学习/深度学习/模式识别/计算机视觉/人工智能算法开发;

(5)手术导航系统及手术机器人研究开发经验;

(6)眼科或脑神经科等医学图像处理研究经验。

4、需提交的申请材料:

(1)本人学习证明和工作简历及联系方式;

(2)其它能证明个人专长或能力的材料。

5、相关待遇:

博士后:年薪30万

研究助理教授:年薪30-45万

6、工作地点:

深圳市南方科技大学

7、单位联系方式:

毕老师 biax@mail.sustech.edu.cn

团队负责人简介:http://faculty.sustech.edu.cn/?cat=29&tagid=liuj

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Contact Address

Room 403, Block 10, Innovation Valley, 1088 Xueyuan Avenue, Shenzhen 518055, P.R. China

Office Phone

075588015223

Email

biax@mail.sustech.edu.cn

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