Li Chen Curriculum Vitae

Last update: Sep 2022

RESEARCH INTERESTS

Medical Image Analysis, Machine Learning, Computer Vision

ACADEMIC QUALIFICATIONS

Sep. 2016 – Aug. 2021	Ph.D. in Electrical and Computer Engineering, University of Washington
	Dissertation: Feature extraction and quantification to explore human vasculature. (PPT) (PDF) Research assistant in Vascular Imaging Lab. Co-advised by Prof. Chun Yuan and Prof. Jenq-Neng Hwang Overall   GPA:  3.89 /4.0
Sep. 2012 – June 2016	B.S. in Electrical Engineering, Fudan University
	Overall   GPA:  3.6 /4.0      Ranking:  9%
Jan. 2015 – May. 2015	Exchange Student in National University of Singapore
	Overall   GPA:  5.0 /5.0

WORK EXPERIENCES

Oct. 2021 – Now	Research Scientist, Philips Research North America
	Ultrasound AI Group, Department of Precision Diagnosis and Image-Guided Therapy, Philips Research Innovation Hub Cambridge MA. Managed by Dr. Alvin Chen.
May – Aug. 2021	Research Intern, Genentech, Inc.
	Early Clinical Development Informatics (ECDi) group. Advised by Dr. Reza Negahdar.
June – Sep. 2020	Research Intern, United Imaging Intelligence America
	Medical AI group. Advised by Dr. Shanhui Sun and Terrence Chen.

CONTRIBUTIONS TO SCIENCE

1. Image processing and analysis for medical image interpretation

The image processing and analysis techniques allow machines to understand the content of images and reveal important information from medical images. For example, by using object tracking method artery of interest from 3D vascular images can be automatically identified, and an artery centerline can be generated for the following up visualization and vessel analysis. Another example is image registration from two time points to observe disease development. Accurate analysis on medical images helps to identify features and patterns in addition to traditional clinical features, so that they can be utilized to identify subjects with health problems, such as identifying people with high risk of plaques and detecting health status from tongue images. Applying these features in future clinical studies might establish a new approach for further our understanding of disease mechanism and prevention.

• Li Chen, Huilin Zhao, Hongjian Jiang, Niranjan Balu, Hiroko Watase, Duygu Baylam Geleri, Xihai Zhao, Rui Li, Jianrong Xu, Thomas S. Hatsukami, Dongxiang Xu, Jenq-Neng Hwang, Chun Yuan. Domain Adaptive and Fully Automated Carotid Artery Atherosclerotic Lesion Detection using an Artificial Intelligence Approach (LATTE) on 3D MRI. Magnetic resonance in medicine (IF:3.6), 2021, 86 (3), Pages 1662-1673.
• Li Chen, Yuxi Lian, Yi Guo, Yuanyuan Wang, Thomas S. Hatsukami, Kristi Pimentel, Niranjan Balu, and Chun Yuan. A vascular image registration method based on network structure and circuit simulation. BMC Bioinformatics, 18(1):229, 2017.
• Li Chen, Wenjin Liu, Gador Canton, Niranjan Balu, Thomas Hatsukami, John C. Waterton, Jenq-Neng Hwang, Chun Yuan. Visualizing and utilizing the latent features of MR vessel wall images using weakly supervised deep learning analysis workflow. 2020 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), 2020, ICC Sydney, Sydney, Australia (17-20 April 2020).
• Li Chen, Dongyi Wang, Yiqin Liu, Xiaohang Gao, Huiliang Shang. A Novel Automatic Tongue Image Segmentation Algorithm: Color Enhancement Method Based on L*a*b* Color Space. 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 990-993, 9-12 Nov. 2015.

2. Machine learning for medical research and clinical applications

The powerful ability of machine learning techniques, especially deep learning techniques are bringing great benefits to medical solutions. I am actively taking the role of bridging the gap between technical and medical society by learning the clinical needs and applying machine learning techniques to clinical applications. I have developed several clinically usable machine learning models to allow clinicians to easily use the advance techniques in their routine work or research. For example, I have developed an automated lumen and outer wall segmentation model using deep learning, which takes 5% of manual review time while having similar performance with expert readers. With that, we can process the whole OAI dataset within two months, a workload of 67 years of manual labeling, and thus we are able to analyze and summarize the vessel wall conditions in 3.5 million knee images. Another example is the high-risk atherosclerotic lesion detection model which is able to identify carotid artery centerlines and highlight the segments with high risk lesions, which is effective in reducing the manual review time and improve the detection sensitivity. Machine learning will definitely make tremendous contributions to the medical society in the future, and I am passionate to be involved in this exciting direction.

• Li Chen, Gador Canton, Wenjin Liu, Daniel S. Hippe, Niranjan Balu, Hiroko Watase, Thomas S. Hatsukami, John C. Waterton, Jenq-Neng Hwang, Chun Yuan. Fully automated and Robust Analysis Technique for Popliteal Artery Vessel Wall Evaluation (FRAPPE) using Neural Network Models from Standardized Knee MRI. Magnetic resonance in medicine, 2020. DOI: 10.1002/mrm.28237
• Li Chen, Jie Sun, Gador Canton, Niranjan Balu, Daniel S. Hippe, Xihai Zhao, Rui Li, Thomas S. Hatsukami, Jenq-Neng Hwang, Chun Yuan. Automated Artery Localization and Vessel Wall Segmentation of Vessel Wall Images using Tracklet Refinement and Polar Conversion . IEEE Access, 2020, 8, Pages 217603-217614
• Li Chen, Yanjun Xie, Jie Sun, Niranjan Balu, Mahmud Mossa-Basha, Kristi Pimentel, Thomas Hatsukami, Jenq-Neng Hwang, and Chun Yuan. 3D intracranial artery segmentation using a convolutional autoencoder. 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 714-717, 2017.

3. Artery structure and blood flow modeling from vascular images

Modeling vascular regions shown in vascular images into a topological network (vasculature tree) is a novel image analysis method to allow quantification of artery structures and blood flow. Quantitative measurements from the vasculature tree, including artery length, volume, tortuosity and signal intensity, provide novel imaging biomarkers for various research topics, such as evaluation of artery and flow differences in a certain population of interest, and identify vascular changes between time points. A series of research have been available since the development and validation of an artery feature extraction tool (iCafe, highlighted in Editor's Pick of the MRM journal). I have developed iCafe, validated its reliability on extracting features from TOF MRA, and applied iCafe on various interesting research projects, for example, exploration of cerebral vasculature declines for elderly in a cross-sectional study. iCafe can also be applied on other imaging sequences (CTA) or vascular beds (peripheral arteries).

• Li Chen, Mahmud Mossa-Basha, Niranjan Balu, Gador Canton, Jie Sun, Kristi Pimentel, Thomas S. Hatsukami, Jenq-Neng Hwang, and Chun Yuan. Development of a quantitative intracranial vascular features extraction tool on 3DMRA using semiautomated open-curve active contour vessel tracing. Magnetic Resonance in Medicine, 79(6):3229-3238, 2018.
• Li Chen, Jie Sun, Daniel S Hippe, Niranjan Balu, Quan Yuan, Isabelle Yuan, Xihai Zhao, Rui Li, Le He, Thomas S Hatsukami, Jenq-Neng Hwang, Chun Yuan. Quantitative Assessment of the Intracranial Vasculature in an Older Adult Population using iCafe (intraCranial Artery Feature Extraction). Neurobiology of Aging, 79:59-65, 2019.
• Li Chen, Wenjin Liu, Niranjan Balu, Mahmud Mossa-Basha, Thomas S. Hatsukami, Jenq-Neng Hwang, Chun Yuan. Deep Open Snake Tracker for Vessel Tracing. MICCAI 2021, the 24th International Conference on Medical Image Computing and Computer Assisted Intervention, 2021, Strasbourg, France (September 27th to October 1st).
• Li Chen, Thomas Hatsukami, Jenq-Neng Hwang, Chun Yuan. Automated Intracranial Artery Labeling using a Graph Neural Network and Hierarchical Refinement. MICCAI 2020, the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention, 2020, Lima, Peru (October 4 - 8, 2020).

RESEARCH EXPERIENCES

Philips Research North America	Oct. 2021 ~ Now
Research Scientist. Ultrasound AI group.	Cambridge, MA
AI Based Medical Ultrasound Imaging Analysis Develop detection and classification models for AI based lung ultrasound diagnosis.
Vascular Imaging Lab & Information Processing Lab, University of Washington	Sep. 2016 ~ Aug. 2021
Research Assistant. Co-advised by Prof. Chun Yuan, Department of Radiology and Bioengineering, and Prof. Jenq-Neng Hwang, Department of Electrical and Computer Engineering	Seattle, WA
Quantitative intracranial artery modeling and vascular feature extraction Developed an artery tracing and labeling tool (iCafe, C++ software, 60k lines) to model arteries and extract cerebral vascular features. A novel artery refinement algorithm through optimization on Curved Planar Reformation view. A novel artery naming algorithms using Graph Neural Network and hierarchical refinement. Created a database of 1000+ scans of cerebral vasculature models. Tool used by 12+ sites on dozens of medical research researches (aging, dementia, artery revascularization, etc.). Three first-author journal papers (1,2,3) and seven conference publications ranging from technical development, validation and medical applications. Editor's pick by Magnetic Resonance in Medicine. iCafe website: http://icafe.clatfd.cn Vessel wall segmentation using convolutional neural networks Proposed an automated vessel wall segmentation and quantification method. (paper) 3D region of interest identification using object tracking (Yolo V2 detector and tracklet refinement). A novel vessel wall segmentation algorithm in polar coordinate system using deep learning. Segmentation with uncertainty scores, proved to be useful in indicating segmentation performance. Trained on more than one thousand subjects of labeled carotid vessel wall contours using convolutional neural network (CNN). Test set performance better than traditional cartesian based CNN methods (U-Net, Mask-RCNN). Automated popliteal vessel wall segmentation and quantification. Developed a fully-automated and robust vessel wall analysis tool (FRAPPE) to segment and quantify popliteal arteries and vessel walls for vascular research. (paper) Processed on The Osteoarthritis Initiative (OAI) dataset with 3.5 Million popliteal artery images. Transfer learning (from the carotid artery model) and active learning techniques to reduce labeling burden while maintaining accuracy. Dice of 0.79 with human contours, only 1.2% images have major errors. Found significant differences in vessel wall thickness measurements between high and low risk subjects. Multi GPU process within 2 months, the workload of 70 years for an expert human reader. Winner for American Heart Association/Amazon Web Services Prize Competition. More technical details:http://clatfd.cn/a/286 Carotid artery atherosclerotic lesion screening using an AI based fully automated workflow based on 3D MRI Proposed a 5-minute automated Magnetic Resonance screening workflow using multiple deep learning models. 3D MERGE as the fast (2 minutes) MR imaging sequence. Image quality assessment using target weighted patches. (joint work with Hongjian Jiang, master student under mentorship) Multi slice multi channel patches for lesion classification. High agreements with an expert radiologist (0.9+ sensitivity/specificity). Assist radiologists by warning potential locations of advance lesions visualized in 3D view. Effective in reducing manual review time for both experts and novice radiologists in clinical reading. Online learning method to reduce labeling labors. Patent filed.
Genentech, Inc.	May ~ Aug. 2021
Research intern. Advised by Dr. Reza Negahdar, Early Clinical Development Informatics (ECDi) group.	South San Francisco, CA
Imaging and non-imaging feature fusion Developed a feature fusion model for improving COVID-19 classification from CTA images. Fusion of imaging and non-imaging features improves COVID classification by 6.6%. Grad-CAM to interpret image region importance.
United Imaging Intelligence America	June ~ Sep. 2020
Research intern. Advised by Dr. Shanhui Sun and Terrence Chen, Medical AI group	Boston, MA
Landmark tracking for stent enhancement A deep learning workflow for balloon marker detection, tracking and stent enhancement. Developed a marker detector with 95% recall / 50% precision / 44 frames per second. Robust marker tracking using graph search with 0.36mm mean distance with manual labels. Iterative process to separate stent and clutter layer for stent enhancement.
Circuit Theory and Application Lab, Fudan University	Oct. 2013 ~ June 2016
Undergraduate Researcher. Advised by: Dr. Huiliang Shang, Associate Professor, Department of Electronic Engineering	Shanghai, China
Capstone research: 'Vascular image registration by circuit simulation'(published in BMC bioinformatics, First Author) A novel algorithm to represent vasculatures as circuits for robust matching. Convert vascular trees into circuits, register using simulated voltages Use Network Structure Index to represent regional graph features Robust registration method tolerates noises and distortions Best undergraduate thesis in Fudan University Research: 'A Novel Automatic Tongue Image Segmentation Algorithm: Color Enhancement Method Based on L*a*b* Color Space'(published in Bioinformatics and Biomedicine (BIBM), 2015 IEEE International Conference on, First Author) Utilize potential advantages of specific characteristics in three color-spaces to find a new method to detect tongue contour in the tongue diagnosis image. In HSV space, using a hue threshold control function to determine a proper threshold value for preliminary separation of tongue region In RGB space, performing color enhancement to obtain a better luminance which is more suitable for tongue segmentation In L*A*B* space, using the luminance sensitivity of L channel to constrain the area of interest Cooperated with Shanghai Traditional Chinese Medicine University and series of local hospitals Research: 'The Application Characteristics of Traditional Chinese Medical Science Treatment on Vertigo Based on Data Mining Apriori Algorithm' (published on IJWMC, First Student Author) To investigate statistical law in Traditional Chinese Medical(TCM) Treatment on vertigo using data mining technique Created a database of TCM treatment prescriptions where 100 cases of prescriptions are selected. Using Apriori algorithm for association rules mining in SPSS to find interrelationships among TCM syndromes, symptoms, and herbal medicine for vertigo, helping research on vertigo using TCM Proposed a topology representation method using circuit simulation for vascular registration. Research: 'An Adaptive Computer-aided Tongue Diagnosis Method using Color-calibration Preprocessing and Multiple Feature Synthesis based on Android' (published on IJWMC, First Student Author) A research on diagnosing disease by taking a picture from tongue based on Android phone. Accuracy and effectiveness corroborated with professional clinicians Used QCGP to solve the problem of white balance Adapted HSV model in Tongue brim pixels searching Adapted inverted pentagonal four-line tongue outline searching and linking algorithm
Adaptive Networks and Control Lab (CAN), Fudan University	Mar. 2014 ~ Mar. 2015
Undergraduate Researcher. Advised by: Prof. Xiang Li, Professor, Department of Electronic Engineering	Shanghai, China
Research: 'An improved method of acquaintance immunization strategy in complex network'(published on JTB (IF:2.116), First Author) A research to find an improved method to effectively immune a virus spreading in complex network. A new Index of NSI is presented to value the structure and importance of nodes in network Improved the classical acquaintance immunization strategy using NSI to protect 14.9% more nodes and decrease the spread rate by 27.6% (compared to classical strategy in our simulation) Simulated in various network structures. Best in most random graph compared to other immunization strategies in the perspective of maximum percentage of infected nodes
Key Laboratory of EMW information, Fudan University	Oct. 2013 ~ Nov. 2014
Undergraduate Researcher. Advised by: Prof. Bin Wang, Professor, Department of Electronic Engineering	Shanghai, China
FDUROP Project: 'The development of an inaccurate graph isomorphism algorithm and its application in prototype machine' (Exhibited on 2014 Shanghai Industrial Exhibition) Building a prototype machine which uses contour extraction algorithms to determine the location of products in images captured from production line and sort them according to their shape. Funded 6000 RMB by FuDan Undergraduate Research Opportunity Program(FDUROP) Cooperated with Shanghai GO-WELL Electrical Technology CO. Used Matlab and OpenCV for the algorithm and executed on multi-platform (PC, raspberry, DSP) Endured noises and overlaps, high recognition of different products on the same production line
Fudan Physic Teaching Lab, Fudan University	Sep. 2013 ~ Dec. 2013
Undergraduate Researcher. Advised by: Prof. Yongkang Le, Professor, Department of Physics	Shanghai, China
Application: 'A remote & online electrical control center using infrared ray based on Arduino' A versatile remote control center which can operate multiple electrical devices using infrared ray. Emit infrared ray instructions under Internet control from remote devices (PC, smartphone, iPad) Can memorize codes of up to 3 infrared control devices A project for the Arduino contest held by Fudan Physic research center

For Whole Research Experience, Link to Project Journey

PUBLICATION

Journal Publications

• [J27] Kaiyu Zhang, Zhensen Chen, Li Chen, Gador Canton, Duygu Baylam Geleri, Baocheng Chu, Yin Guo, Daniel S.Hippe, Kristi D. Pimentel, Niranjan Balu, Thomas S. Hatsukam, Chun Yuan. Alterations in cerebral distal vascular features and effect on cognition in a high cardiovascular risk population: A prospective longitudinal study. Magnetic Resonance Imaging (IF:3.13), 2023, 98 (May 2023), Pages 36-43. DOI: 10.1016/j.mri.2022.12.011

• [J26] Anders Gould, Zhensen Chen, Duygu Baylam Geleri, Niranjan Balu, Li Chen, Baocheng Chu, Kristi Pimentel, Gador Canton, Thomas Hatsukami, Chun Yuan. Associations of Intracranial Vascular Features on Non-contrast Enhanced MRA with Cognitive Impairment (P15-10.001). Neurology (IF:9.901), 2022, 98 (18 Supplement).

• [J25] Zhensen Chen, Anders Gould, Duygu Baylam Geleri, Niranjan Balu, Li Chen, Baocheng Chu, Kristi Pimentel, Gador Canton, Thomas S Hatsukami, Chun Yuan. Associations of intracranial artery length and branch number on non-contrast enhanced MRA with cognitive impairment in individuals with carotid atherosclerosis. Scientific Reports (IF:4.996), 2022, 2022, Pages 7456. DOI: 10.1038/s41598-022-11418-y

• [J24] Jie Sun, Mahmud Mossa-Basha, Gador Canton, Niranjan Balu, Yin Guo, Li Chen, Dongxiang Xu, Daniel S Hippe, Kristi D Pimentel, Thomas S Hatsukami, Chun Yuan. Characterization of non-stenotic plaques in intracranial arteries with multi-contrast, multi-planar vessel wall image analysis. Journal of Stroke and Cerebrovascular Diseases (IF:2.136), 2022, 31 (10), Pages 106719. DOI: 10.1016/j.jstrokecerebrovasdis.2022.106719

• [J23] Yin Guo, Gador Canton, Li Chen, Jie Sun, Duygu Baylam Geleri, Niranjan Balu, Dongxiang Xu, Mahmud Mossa-Basha, Thomas S. Hatsukami, Chun Yuan. Multi‐Planar, Multi‐Contrast and Multi‐Time Point Analysis Tool MOCHA for Intracranial Vessel Wall Characterization in Journal of Magnetic Resonance Imaging. Journal of Magnetic Resonance Imaging (IF:4.813), 2022, 56 (3), Pages 944-955. DOI: 10.1002/jmri.28087

• [J22] Lanxin Ji, Yuhui Xiong, Le He, Li Chen, Xue Zhang, Zhensen Chen, Xuesong Li, Huilin Zhao, Manabu Shirakawa, Chun Yuan, Yu Ma. Effects of Levodopa Therapy on Cerebral Arteries and Perfusion in Parkinson’s Disease Patients. Journal of Magnetic Resonance Imaging (IF:4.8), 2021, 55 (3), Pages 943-953. DOI: 10.1002/jmri.27903

• [J21] Wenjin Liu, Xiaoqin Huang, Xuebing Liu, Lulu Wang, Zhensen Chen, Dakota Ortega, Li Chen, Jie Sun, Thomas S Hatsukami, Chun Yuan, Haige Li, junwei yang. Urinary Sodium and Potassium Excretion and Cerebrovascular Health: A Multimodal Imaging Study. European Journal of Nutrition (IF:4.7), 2021, 60 (8), Pages 4555–4563. DOI: 10.1007/s00394-021-02612-1

• [J20] Duygu Baylam Geleri, Hiroko Watase, Baocheng Chu, Li Chen, Huilin Zhao, Xihai Zhao, Thomas Hatsukami, and Chun Yuan. Detection of Advanced Lesions on Carotid Arteries using 3D-MERGE Magnetic Resonance Imaging as a Screening Tool. Stroke (IF:7.2), 2021, 53 (1), Pages 194–200. DOI: 10.1161/STROKEAHA.120.032505

• [J19] Li Chen, Dennis W.W. Shaw, Stephen R. Dager, Neva M Corrigan, Baocheng Chu, Natalia Maria Kleinhans, Patricia Kuhl, Jenq-Neng Hwang and Chun Yuan. Quantitative Assessment of the Intracranial Vasculature of Infants and Adults using iCafe (intraCranial Artery Feature Extraction). Frontiers in Neurology (IF:2.9), 2021, 28 May 2021. DOI: 10.3389/fneur.2021.668298 (pdf)

• [J18] Anders Gould, Zhensen Chen, Duygu Baylam Geleri, Niranjan Balu, Zechen Zhou, Li Chen, Baocheng Chu, Kristi Pimentel Gador Canton Thomas Hatsukami, Chun Yuan. Vessel length on SNAP MRA and TOF MRA is a potential imaging biomarker for brain blood flow. Magnetic Resonance Imaging (IF:2.1), 2021, 79 (June 2021), Pages 20-27. DOI: 10.1016/j.mri.2021.02.012

• [J17] Gador Canton, Daniel Hippe, Li Chen, John Waterton, Wenjin Liu, Hiroko Watase, Niranjan Balu, Jie Sun, Thomas Hatsukami, Chun Yuan. Atherosclerotic Burden and Remodeling Patterns of the Popliteal Artery as detected in the MRI Osteoarthritis Initiative Dataset. JAHA: Journal of the American Heart Association (IF:4.67), 2021, 10 (11). DOI: 10.1161/JAHA.120.018408

• [J16] Li Chen, Huilin Zhao, Hongjian Jiang, Niranjan Balu, Hiroko Watase, Duygu Baylam Geleri, Xihai Zhao, Rui Li, Jianrong Xu, Thomas S. Hatsukami, Dongxiang Xu, Jenq-Neng Hwang, Chun Yuan. Domain Adaptive and Fully Automated Carotid Artery Atherosclerotic Lesion Detection using an Artificial Intelligence Approach (LATTE) on 3D MRI. Magnetic resonance in medicine (IF:3.6), 2021, 86 (3), Pages 1662-1673. DOI: 10.1002/MRM.28794

• [J15] Wenjin Liu, Zhensen Chen, Dakota Ortega, Xuebing Liu, Xiaoqin Huang, Lulu Wang, Li Chen, Jie Sun, Thomas S Hatsukami, Chun Yuan, Haige Li, Junwei Yang. Arterial Elasticity, Endothelial Function and Intracranial Vascular Health: A Multimodal MRI Study. Journal of Cerebral Blood Flow and Metabolism (IF:5.7), 2020, 41 (6), Pages 1390-1397. DOI: 10.1177/0271678X20956950

• [J14] Zhensen Chen, Li Chen, Manabu Shirakawa, Wenjin Liu, Dakota Ortega, Jinmei Chen, Niranjan Balu, Theodore Trouard, Thomas Hatsukami, Wei Zhou, Chun Yuan. Intracranial vascular feature changes in time of flight MR angiography in patients undergoing carotid revascularization surgery. Magnetic Resonance Imaging (IF:2.1), 2020, 75 (January 2021), Pages 45-50. DOI: 10.1016/j.mri.2020.10.004

• [J13] Wenjin Liu, Xiaoqin Huang, Xuebing Liu, Dakota Ortega, Li Chen, Zhensen Chen, Jie Sun, Lulu Wang, Thomas S. Hatsukami, Chun Yuan, Haige Li & Junwei Yang. Uncontrolled hypertension associates with subclinical cerebrovascular health globally: a multimodal imaging study. European Radiology (IF:4.1), 2020, 31 (14 September 2020), Pages 2233–2241. DOI: 10.1007/s00330-020-07218-5

• [J12] Daniel Hippe, Niranjan Balu, Li Chen, Gador Canton, Wenjin Liu, Hiroko Watase, John Waterton, Thomas Hatsukami, Jenq-Neng Hwang, Chun Yuan. Confidence weighting for robust automated measurements of popliteal vessel wall MRI. Circulation: Genomic and Precision Medicine (IF:4.9), 2020, 13 (1), Pages 39-41. DOI: 10.1161/CIRCGEN.119.002870

• [J11] Li Chen, Stephen R. Dager, Dennis W.W. Shaw, Neva M. Corrigan, Mahmud Mossa-Basha, Kristi D. Pimentel, Natalia M. Kleinhans, Patricia K. Kuhl, Jenq-Neng Hwang, Chun Yuan. A Novel Algorithm for Refining Cerebral Vascular Measurements in Infants and Adults. Journal of Neuroscience Methods (IF:2.8), 2020, 340 (1 July 2020), Pages 108751. DOI: 10.1016/j.jneumeth.2020.108751

• [J10] Li Chen, Jie Sun, Gador Canton, Niranjan Balu, Daniel S. Hippe, Xihai Zhao, Rui Li, Thomas S. Hatsukami, Jenq-Neng Hwang, Chun Yuan. Automated Artery Localization and Vessel Wall Segmentation of Vessel Wall Images using Tracklet Refinement and Polar Conversion . IEEE Access, 2020, 8, Pages 217603-217614. DOI: 10.1109/ACCESS.2020.3040616 (pdf) (code)

• [J9] Li Chen, Gador Canton, Wenjin Liu, Daniel S. Hippe, Niranjan Balu, Hiroko Watase, Thomas S. Hatsukami, John C. Waterton, Jenq-Neng Hwang, Chun Yuan. Fully automated and Robust Analysis Technique for Popliteal Artery Vessel Wall Evaluation (FRAPPE) using Neural Network Models from Standardized Knee MRI. Magnetic resonance in medicine (IF:3.6), 2020, 84, Pages 2147–2160. DOI: 10.1002/mrm.28237 (pdf)

• [J8] Qiang Zhang, Zhensen Chen, Shuo Chen, Xinke Liu, Jia Ning, Yongjun Han, Li Chen, Le He, Xihai Zhao, Yuhui Xiong, Hua Guo, Chun Yuan, Rui Li, Huijun Chen. Angiographic contrast mechanism comparison between Simultaneous Non-contrast Angiography and intraPlaque hemorrhage (SNAP) sequence and Time of Flight (TOF) sequence for intracranial artery. Magnetic Resonance Imaging (IF:2.1), 2019, 66 (February 2020), Pages 199-207. DOI: 10.1016/j.mri.2019.09.001

• [J7] Li Chen, Jie Sun, Daniel S Hippe, Niranjan Balu, Quan Yuan, Isabelle Yuan, Xihai Zhao, Rui Li, Le He, Thomas S. Hatsukami, Jenq-Neng Hwang, Chun Yuan. Quantitative Assessment of the Intracranial Vasculature in an Older Adult Population using iCafe (intraCranial Artery Feature Extraction). Neurobiology of Aging (IF:4.4), 2019, 79 (July 2019), Pages 59-65. DOI: 10.1016/j.neurobiolaging.2019.02.027 (pdf)

• [J6] Li Chen, Mahmud Mossa-Basha, Jie Sun, Daniel S Hippe, Niranjan Balu, Quan Yuan, Kristi Pimentel, Thomas S. Hatsukami, Jenq-Neng Hwang, Chun Yuan*. Quantification of morphometry and intensity features of intracranial arteries from 3D TOF MRA using the intracranial artery feature extraction (iCafe): A reproducibility study. Magnetic Resonance Imaging (IF:2.1), 2019, 57 (April 2019), Pages 293-302. DOI: 10.1016/j.mri.2018.12.007 (pdf)

• [J5] Li Chen, Mahmud Mossa‐Basha, Niranjan Balu, Gador Canton, Jie Sun, Kristi Pimentel, Thomas S Hatsukami, Jenq‐Neng Hwang, Chun Yuan. Development of a quantitative intracranial vascular features extraction tool on 3D MRA using semiautomated open‐curve active contour vessel tracing. Magnetic resonance in medicine (IF:3.9), 2018, 79 (6), Pages 3229-3238. DOI: 10.1002/mrm.26961 (Editor's pick) (pdf) (ppt)

• [J4] Li Chen, Yuxi Lian, Yi Guo, Yuanyuan Wang, Thomas S Hatsukami, Kristi Pimentel, Niranjan Balu, Chun Yuan. A vascular image registration method based on network structure and circuit simulation. BMC bioinformatics (IF:2.5), 2017, 18 (1), Pages 229. DOI: 10.1186/s12859-017-1649-1 (pdf)

• [J3] Miao Wang, Li Chen, Yanjun Huang, Lei Zhang, Zihao Zhang, Jie Ding, Huiliang Shang. The application characteristics of traditional Chinese medical science treatment on vertigo based on data mining Apriori algorithm. International Journal of Wireless and Mobile Computing  (IF:1.2), 2015, 9 (4), Pages 349-354. DOI: 10.1504/IJWMC.2015.074041

• [J2] Miao Wang, Li Chen, Qing Li, Dongyi Wang, Yiqin Liu, Yi Zhang, Shoulan Bing, Huiliang Shang. An adaptive computer-aided tongue diagnosis method using colour-calibration preprocessing and multiple feature synthesis based on Android platform. International Journal of Wireless and Mobile Computing (IF:1.2), 2015, 9 (3), Pages 240-249. DOI: 10.1504/IJWMC.2015.073107

• [J1] Li Chen, Dongyi Wang. An improved acquaintance immunization strategy for complex network. Journal of theoretical biology (IF:2.1), 2015,  (385), Pages 58-65. DOI: 10.1016/j.jtbi.2015.07.037 (pdf) (ppt)

Conference Publications

• [C11] Gary Y. Li, Li Chen, Mohsen Zahiri, Naveen Balaraju, Shubham Patil, Courosh Mehanian, Cynthia Gregory, Kenton Gregory, Balasundar Raju, Jochen Kruecker, Alvin Chen. Weakly Semi-supervised Detector-based Video Classification with Temporal Constraints for Lung Ultrasound. ICCV 2023 Workshop on Computer Vision for Automated Medical Diagnosis, 2023, Paris Convention Center in Paris, France.  (October 2-3, 2023).

• [C10] Jiahong Ouyang, Li Chen*, Gary Y. Li, Naveen Balaraju, Shubham Patil, Courosh Mehanian, Sourabh Kulhare, Rachel Millin, Kenton W. Gregory, Cynthia R. Gregory, Meihua Zhu, David O. Kessler, Laurie Malia, Almaz Dessie, Joni Rabiner, Di Coneybeare, Bo Shopsin, Andrew Hersh, Cristian Madar, Jeffrey Shupp, Laura S. Johnson, Jacob Avila, Kristin Dwyer, Peter Weimersheimer, Balasundar Raju, Jochen Kruecker, and Alvin Chen. Weakly Semi-Supervised Detection in Lung Ultrasound Videos. The 28th biennial international conference on Information Processing in Medical Imaging, 2023, San Carlos de Bariloche, Argentina (18 to 23 June 2023).

• [C9] Li Chen*, Jonathan Rubin*†, Jiahong Ouyang, Naveen Balaraju, Shubham Patil, Courosh Mehanian, Sourabh Kulhare, Rachel Millin, Kenton W. Gregory, Cynthia R. Gregory, Meihua Zhu, David O. Kessler, Laurie Malia, Almaz Dessie, Joni Rabiner, Di Coneybeare, Bo Shopsin, Andrew Hersh, Cristian Madar, Jeffrey Shupp, Laura S. Johnson, Jacob Avila, Kristin Dwyer, Peter Weimersheimer, Balasundar Raju, Jochen Kruecker, Alvin Chen. Contrastive self-supervised learning for spatio-temporal analysis of lung ultrasound videos. IEEE International Symposium on Biomedical Imaging (ISBI) , 2023, Cartagena, Colombia (April 18 - 21, 2023).

• [C8] Luojie Huang, Yikang Liu, Li Chen, Eric Z. Chen, Xiao Chen, Shanhui Sun. Robust Landmark-based Stent Tracking in X-ray Fluoroscopy. European Conference on Computer Vision, 2022, Tel Aviv, Israel (October 23-27).

• [C7] Li Chen, Wenjin Liu, Niranjan Balu, Mahmud Mossa-Basha, Thomas S. Hatsukami, Jenq-Neng Hwang, Chun Yuan. Deep Open Snake Tracker for Vessel Tracing. MICCAI 2021, the 24th International Conference on Medical Image Computing and Computer Assisted Intervention, 2021, Strasbourg, France (September 27th to October 1st). DOI: 10.1007/978-3-030-87231-1_56

• [C6] Li Chen, Thomas Hatsukami, Jenq-Neng Hwang, Chun Yuan. Automated Intracranial Artery Labeling using a Graph Neural Network and Hierarchical Refinement. MICCAI 2020, the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention, 2020, Lima, Peru (October 4 - 8, 2020). DOI: 10.1007/978-3-030-59725-2_8 (pdf) (ppt) (code)

• [C5] Hongjian Jiang, Li Chen, Dongxiang Xu, Huilin Zhao, Hiroko Watase, Xihai Zhao, Rui Li, Chun Yuan. A Target-Oriented and Multi-Patch Based Framework for Image Quality Assessment on Carotid Artery MRI. Medical Imaging 2020: Image Processing. SPIE, 2020, Marriott Marquis Houston, Houston, Texas, United States  (February 15 - 20). DOI: 10.1117/12.2549473

• [C4] Li Chen, Gaoang Wang, Niranjan Balu, Mahmud Mossa-Basha, Xihai Zhao, Rui Li, LeHe, Thomas S. Hatsukami, Jenq-Neng Hwang, Chun Yuan. Simultaneous Intracranial Artery Tracing and Segmentation from Magnetic Resonance Angiography by Joint Optimization from Multiplanar Reformation. Machine Learning and Medical Engineering for Cardiovascular Health and Intravascular Imaging and Computer Assisted Stenting, First International Workshop, MLMECH 2019, and 8th Joint International Workshop, CVII-STENT 2019, Held in Conjunction with MICCAI, 2019, Shenzhen, China (October 13), Pages 201-209. DOI: 10.1007/978-3-030-33327-0 (pdf) (ppt)

• [C3] Li Chen, Yanjun Xie, Jie Sun, Niranjan Balu, Mahmud Mossa-Basha, Kristi Pimentel, Thomas S Hatsukami, Jenq-Neng Hwang, Chun Yuan. 3D intracranial artery segmentation using a convolutional autoencoder. 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2017, Kansas City, MO, USA (November 13 - 16). DOI: 10.1109/BIBM.2017.8217741 (pdf) (ppt)

• [C2] Miao Wang, Jiayun Li, Li Chen, Yanjun Huang, Qiang Zhou, Lijuan Che, Huiliang Shang. The Study of the Compatibility Rules of Traditional Chinese Medicine Based on Apriori and HMETIS Hypergraph Partitioning Algorithm. VLDB Workshop on Big Graphs Online Querying, 2015, Waikoloa, HI, USA (August 31 – September 4), Pages 16-31. DOI: 10.1007/978-3-319-41576-5_2 (pdf)

• [C1] Li Chen, Dongyi Wang, Yiqin Liu, Xiaohang Gao, Huiliang Shang. A novel automatic tongue image segmentation algorithm: Color enhancement method based on L* a* b* color space. Bioinformatics and Biomedicine (BIBM), 2015 IEEE International Conference on, 2015, Washington D.C., USA ( November 9-12), Pages 990-993. DOI: 10.1109/BIBM.2015.7359818 (pdf) (ppt)

Conference/Workshop Oral Presentation

• [P3] Li Chen, Wenjin Liu, Gador Canton, Niranjan Balu, Thomas Hatsukami, John C. Waterton, Jenq-Neng Hwang, Chun Yuan. Visualizing and utilizing the latent features of MR vessel wall images using weakly supervised deep learning analysis workflow. 2020 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), 2020, ICC Sydney, Sydney, Australia (17-20 April 2020). (Magna Cum Laude Merit Award) (pdf) (ppt)

• [P2] Li Chen, Huilin Zhao, Niranjan Balu, Xihai Zhao, Rui Li, Jenq-Neng Hwang, Chun Yuan. Carotid Artery Localization and Lesion Detection on 3D-MERGE MRI through Online Learning.. Society for Magnetic Resonance Angiography 30th Annual International Conference, 2018, University of Glasgow, Glasgow, Scotland (August 29-31).

• [P1] Li Chen, Jie Sun, Niranjan Balu, Thomas S. Hatsukami, Mahmud MossaBasha, Kristi D. Pimentel, Jenq-Neng Hwang, Chun Yuan. Automated detection and labeling of the intracranial arterial tree in routine MR angiography: A machine learning approach enhanced with structural saliency. Radiological Society of North America's 103rd Scientific Assembly and Annual Meeting, 2017, McCormick Place, Chicago, Illinois (November 26 - December 1).

Invited Talks

• [T4] Li Chen. Fully automated and Robust Analysis Technique for Popliteal Artery Vessel Wall Evaluation (FRAPPE) using Neural Network Models from Standardized Knee MRI. Imaging Elevated: Utah Symposium for Emerging Investigators , 2020, October 7-9, 2020 • Salt Lake City, UT.

• [T3] Li Chen. Image analysis and AI/deep learning applications on vascular research. Invited talk, 2019, Renji Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China (October 9).

• [T2] Li Chen. Looking into intracranial artery map with big data and machine learning. Intelligent Medical Imaging Symposium, 2018, Tsinghua University, Beijing, China (July 1).

• [T1] Li Chen. Development of a Quantitative Intracranial Vascular Features Extraction Tool on 3D MRA Using Semi-automated Open-Curve Active Contour Vessel Tracing. UW-Philips MRX, 2017, University of Washington (September 22).

Preprints

• [X2] Li Chen, Jie Sun, Gador Canton, Niranjan Balu, Xihai Zhao, Rui Li, Thomas S. Hatsukami, Jenq-Neng Hwang, Chun Yuan. Automated Artery Localization and Vessel Wall Segmentation of Magnetic Resonance Vessel Wall Images using Tracklet Refinement and Polar Conversion. arXiv preprint, 2019,  (arXiv: 1909.02087). (pdf)

• [X1] Li Chen, Yanjun Xie, Jie Sun, Niranjan Balu, Mahmud Mossa-Basha, Kristi Pimentel, Thomas S Hatsukami, Jenq-Neng Hwang, Chun Yuan. Y-net: 3D intracranial artery segmentation using a convolutional autoencoder. arXiv preprint, 2017,  (arXiv: 1712.07194). (pdf)

Conference Posters/E-posters

• [A18] Nhat Hoang, Henry Wang, Sahin Bogachan, Muhammad Waqas Khan, Abrar Faiyaz, Meera Singh, Jinjiang Pang, Shumin Wang, Li Chen, Chun Yuan, Jianhui Zhong, Hongmei Yang, Md Nasir Uddin, and Giovanni Schifitto. Effects of HIV-associated chronic inflammation on intracranial vessels using semi-automatic segmentation of MRA cerebrovascular features. 2023 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), 2023, Toronto, Canada (3-8 June).

• [A17] Alvin Chen, Shubham Patil, Mohsen Zahiri, Li Chen, Bryson Hicks, Nikolai Schnittke, Meihua Zhu, Jeffrey Shupp, Kenton Gregory, Jochen Kruecker, Balasundar Raju. Artificial Intelligence Model to Identify Pleural Line Abnormalities in Lung Ultrasound. American College of Emergency Physicians 2023 Scientific Assembly, 2023, Philadelphia (Oct. 9-12).

• [A16] Yin Guo, Li Chen, Dongxiang Xu, Rui Li, Xihai Zhao, Thomas S. Hatsukami, Chun Yuan. AI-based Computer-Aided System for Cardiovascular Disease Evaluation (AI-CASCADE) forcarotid tissue quantification. 2021 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), 2021, Vancouver, Canada (15-20 May).

• [A15] Kaiyue Tao, Li Chen, Niranjan Balu, Gador Canton, Wenjin Liu, Thomas S. Hatsukami, Chun Yuan. Exploring feature space of MR vessel images with limited data annotations through metriclearning and episodic training. 2021 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), 2021, Vancouver, Canada (15-20 May).

• [A14] Niranjan Balu, Wenjin Liu, Zhensen Chen, Anders Gould, Dan S Hippe, Li Chen, Binbin Sui, Mi Shen, Peiyi Gao, Thomas S Hatsukami, Chun Yuan. Reproducibility of quantitative measures of intracranial arterial geometry: dependence onsequence and scanner platform diferences. 2021 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), 2021, Vancouver, Canada (15-20 May).

• [A13] Zhensen Chen, Li Chen, Manabu Shirakawa, Wenjin Liu, Dakota Ortega, Jinmei Chen, Niranjan Balu, Theodore Trouard, Thomas S Hatsukami, Wei Zhou, and Chun Yuan. Flow measurement with time of flight (TOF) in patients undergoing carotid revascularization: A comparison with arterial spin labeling (ASL). 2020 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), 2020, ICC Sydney, Sydney, Australia (17-20 April 2020).

• [A12] Yuhui Xiong, Lanxin Ji, Le He, Li Chen, Xue Zhang, Zhensen Chen, Xuesong Li, Huilin Zhao, Manabu Shirakawa, Chun Yuan, Yu Ma, and Hua Guo. Effects of Levodopa Therapy on Cerebral Arteries and Brain Tissue Perfusion in Parkinson’s Disease Patients. 2020 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), 2020, ICC Sydney, Sydney, Australia (17-20 April 2020).

• [A11] Gador Canton, Hiroko Watase, Josh Liu, Li Chen, Yin Guo, Yongjun Wang, Chun Yuan. Multiplanar reconstruction of intracranial arteries: luminal morphological characterization of atherosclerosis. 2020 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), 2020, ICC Sydney, Sydney, Australia (17-20 April 2020).

• [A10] Ke Han, Li Chen, Duygu Baylam Geleri, Mahmud Mossa-basha, Thomas Hatsukami, Chun Yuan. Deep-learning based Significant Stenosis detection from Multiplanar reformatted Images of traced Intracranial arteries. American Society of Neuroradiology 58th Annual Meeting, 2020, Las Vegas (May 30 – June 4). (pdf)

• [A9] Li Chen, Duygu Baylam Geleri, Jie Sun, Hiroko Watase, Jiarui Cai, Yin Guo, Niranjan Balu, Dongxiang Xu, Thomas Hatsukami, Yongjun Wang, Jenq-Neng Hwang, Chun Yuan. Multi-planar, multi-contrast and multi-timepoint analysis tool (MOCHA) for intracranial vessel wall imaging review. 2020 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), 2020, ICC Sydney, Sydney, Australia (17-20 April 2020). (pdf) (ppt)

• [A8] Niranjan Balu, Li Chen, Thoetphum Benyakorn, Daniel S Hippe, Henrik Haraldsson, Warren Gasper, David Saloner, Chun Yuan, Thomas Hatsukami. Quantitative measurements of decreased arterial collateralization and branching in peripheral artery disease. 2019 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), 2019, Palais des congrès de Montréal, Montréal, QC, Canada (May 11-16). (pdf)

• [A7] Manabu Shirakawa, Li Chen, Niranjan Balu, Wenjin Liu, Dakota Ortega, Jinmei Chen, Theodore Trouard, Diane Bock, Wei Zhou, Chun Yuan, Thomas S Hatsukami. Quantitative assessment of cerebrovascular structure after carotid revascularization using intraCranial Artery Feature Extraction (iCafe) Technique. 2019 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), 2019, Palais des congrès de Montréal, Montréal, QC, Canada (May 11-16). (pdf)

• [A6] Li Chen, Thoetphum Benyakorn, Gador Canton, Niranjan Balu, Thomas S Hatsukami, Jenq-Neng Hwang, Chun Yuan. Development of a Quantitative Assessment tool for Peripheral Artery Feature Extraction (pCafe). 2019 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), 2019, Palais des congrès de Montréal, Montréal, QC, Canada (May 11-16). (pdf)

• [A5] Li Chen, Thomas Grabowski, Eric B Larson, Paul Crane, Thomas S Hatsukami, Jenq-Neng Hwang, Chun Yuan, Niranjan Balu. Quantitative Intracranial Vasculature Assessment to detect dementia using the intraCranial Artery Feature Extraction (iCafe) Technique. 2019 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), 2019, Palais des congrès de Montréal, Montréal, QC, Canada (May 11-16). (Magna Cum Laude Merit Award) (pdf)

• [A4] Li Chen, Huilin Zhao, Niranjan Balu, Xihai Zhao, Rui Li, Jianrong Xu, Thomas S Hatsukami, Jenq-Neng Hwang, Chun Yuan. Carotid Artery Localization and Lesion Classification on 3D-MERGE MRI using Neural Network and Object Tracking methods. 2019 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), 2019, Palais des congrès de Montréal, Montréal, QC, Canada (May 11-16). (pdf) (ppt)

• [A3] Li Chen, Jie Sun, Wei Zhang, Thomas S Hatsukami, Jianrong Xu, Jenq-Neng Hwang, Chun Yuan. Automatic Segmentation of Carotid Vessel Wall Using Convolutional Neural Network. 2018 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), 2018, Paris Expo Porte de Versailles, Paris, France (June 16-21). (pdf)

• [A2] Li Chen, Quan Yuan, Niranjan Balu, Isabelle Yuan, Daniel S Hippe, Jie Sun, Xihai Zhao, Rui Li, Le He, Jenq-Neng Hwang, Chun Yuan. Quantitative Assessment of the Intracranial Vasculature of an Elderly Population using the intraCranial Artery Feature Extraction (iCafe) Technique. 2018 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), 2018, Paris Expo Porte de Versailles, Paris, France (June 16-21).

• [A1] Li Chen, Mahmud Mossa-Basha, Daniel S Hippe, Jie Sun, Niranjan Balu, Kristi D. Pimentel, Thomas S Hatsukami, Jenq-Neng Hwang, Chun Yuan. Quantification of Morphometry and Intensity Features of Intracranial Arteries from 3D TOF MRA: A Reproducibility Study. 2018 Annual Meeting of International Society for Magnetic Resonance in Medicine (ISMRM), 2018, Paris Expo Porte de Versailles, Paris, France (June 16-21).

Patents

ACADEMIC SERVICE

Journal Reviewer	IEEE Transactions on Medical Imaging, Journal of Biomedical and Health Informatics, Computers in Biology and Medicine, IEEE Access, Artificial Intelligence in Medicine, Medical & Biological Engineering & Computing, The International Journal of Cardiovascular Imaging, Stroke and Vascular Neurology, American Journal of Neuroradiology, Magnetic Resonance Imaging, Electronics and Telecommunications Research Institute (ETRI) Journal, PLOS ONE, International Journal of Modern Physics B.
Conference Reviewer	the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), The AICity 2020 CVPR Workshop.
Challenge Organizer	Carotid Artery Vessel Wall Segmentation Challenge. (Endorsed by SMRA 2021 and MICCAI 2021)

AWARDS

2007-2009	Shanghai AVR single chip   programming contest (First prize in all three years)
2009,   2011	"INTEL" Innovation Contest in Shanghai
2009	Future Engineering Contest in Shanghai
2009-2015	Six consecutive years of Shu Ping Scholarship(top 3%)
2012	Fudan University Excellent Freshman Scholarship(top 5%)
2013-2014	Two consecutive years of Fudan university scholarship(top 15%)
2015	Mathematical Contest in Modeling 2015 (Meritorious Winner, top 10%)
2018	GSFEI Travel Funding, University of Washington
2018	Travel Stipend Awards, SMRA
2018	Outstanding Research Award, OCSMRM
2018, 2019, 2020	ISMRM Annual Meeting & Exhibition Stipend
2019, 2020	Magna Cum Laude Merit Award, ISMRM
2019	Winner for the AHA-AWS award at the 2019 American Heart Association Scientific Meeting

ADVISORS

Chun Yuan

Professor — Department of Radiology and Bioengineering, University of Washington,
From 2016.9 — 2021.8

Researches on Magnetic Resonance Imaging, Vulnerable Plaque/Vessel Wall Imaging and Analysis, Cardiovascular Disease Analysis and Investigation, Vessel Imaging of Vascular Cognitive Impairment and Dementia, MRI Sequence Development and Image Reconstruction, Vessel Image Processing With AI, Machine Learning, and Deep Learning.

Email: cyuan@uw.edu

Experience with me:

             Course: MRI & ULTRASOUND
             PhD thesis co-chair.

Jenq-Neng Hwang

Professor — Department of Electrical & Computer Engineering University of Washington,
From 2016.9 — 2021.8

Researches on Image/video signal processing, Multimedia network and QoS, Statistical pattern recognition.

Email: hwang@uw.edu

Experience with me:

             PhD thesis co-chair.

Huiliang Shang

Accosiate Professor — Department of Electronic Engineering Fudan University,
From 2013.10 — 2016.6

Researches on image processing, Biomedical topics, Traditional Chinese medicine, Robotic, Computer vision, visible light communication, Circuit theory.

Email: shanghl@fudan.edu.cn

Experience with me:

             Course: Circuit Theory
             Four papers about Biomedical Image processing
             LED position car etc.

Bin Wang

Professor — Department of Electronic Engineering, Fudan University
From 2013.10 — 2014.11

Researches on image processing, signal, pattern recongnition, intelligent information proessing and brain science

Email: wangbin@fudan.edu.cn

Experience with me:

             Course: Probability

             The FDUROP project about image processing

Xiang Li

Professor — Department of Electronic Engineering, Fudan University
From 2014.3 — 2015.3

Researches on complex network and multi-agent systems.

Email: lix@fudan.edu.cn

Experience with me:

             Course: Introduction to Network Science

             Paper about immunization network

Yi Guo

Professor — Department of Electronic Engineering , Fudan University,
From 2015.8 — 2016.6

Researches on Medical image and signal processing, Medical ultrasonics.

Email: guoyi@fudan.edu.cn

Experience with me:

             Course: Medical Imaging
             Capstone research advisor
             One paper on vascualr registration

Yuanyuan Wang

Professor — Department of Electronic Engineering , Fudan University,
From 2015.8 — 2016.6

Researches on Medical image and signal processing, Medical ultrasonics.

Email: yywang@fudan.edu.cn

Experience with me:

             Course: Signal and System
             Final year project research group advisor
             

ACTIVITIES

2012-2013	Volunteer teaching in Shanghai Sunflower Weekend School, English Junior class.
2012-2014	Fudan Student Union, Department of Information. Technical director in 2014.
2014.7	Volunteer teaching in Yunnan. Lecturer in Paper cutting and Handwork (Build a gravity toy car)
2014-2015	Technical group of Shu Ping Scholarship Foundation. Developed online scholarship application system.
2017-2018	Trainee Member, Radiological Society of North America (RSNA)
2015-2021	IEEE student member.
2017-2021	Trainee Member, International Society for Magnetic Resonance in Medicine (ISMRM).
2019-2020	Student member, American Heart Association
2019-2021	Student member, Society for Medical Image Computing and Computer Assisted Intervention.