Feng Patrick Li
Octobor 2013
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Curriculum Vitae
Feng Patrick Li
PhD candidate
Imaging Research Laboratories,
Robarts Research Institute
Biomedical Engineering Graduate Program,
The University of Western Ontario
100 Perth Drive, PO Box 5015, London ON N6A 5K8
Tel: (519) 931-5777*24350 (Robarts), (519) 854-4687 (Mobile)
fli@robarts.ca
EDUCATION
2009-
PhD student (Biomedical Engineering)
Robarts Research Institute, Western University, London, Canada
Supervisor: Terry M. Peters, PhD, FCCPM, FIEEE
Project:
Dynamic Image Processing for Guidance of Off-pump
Beating Heart Interventions
2007-2009
MSc Computer Application Technology 2009
Shanghai Jiao Tong University, Shanghai, China
Supervisor: Lixu Gu, PhD
Project:
A Minimally Supervised Classification Method Based on
Statistical and Spatial Information and Its Application in
Liver Segmentation
2005-2008
MSc Computer Science 2008
Technical University of Berlin, Berlin, Germany
Supervisors: Heinz U. Lemke, PhD
Michel A. Audette, PhD
Project:
2D Gaussian-Mixture-Based Bayesian Level Sets for Head
CT Data Classification
2002-2006
BSc Computer Science 2006
Shanghai Jiao Tong University, Shanghai, China
POSITIONS
2010-
The University of Western Ontario
Graduate Teaching Assistant
Course: Programming Fundamentals for Engineers
Lecturer: Quazi Mehbubar Rahman, PhD
Feng Patrick Li
Octobor 2013
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2007
Innovation Centre Computer Assisted Surgery, University of Leipzig
Internship in Therapy Imaging and Model Management System (TIMMS)
group with Dr. Michel Audette
2005
Lab of Image Guided Surgery and Therapy,
Shanghai Jiao Tong University
Internship in soft tissue modelling group with Jianfeng Xu
HONOURS AND AWARDS
2014
1sr prize, scientific poster competition at Imaging Network Ontario 2014
2010, 2011
Computer-Assisted Medical Intervention (CAMI) Training Program
Scholarship
2011-2013
CIHR Strategic Training Fellow Scholarship
2003, 2004
People Scholarship in Shanghai Jiao Tong University
INVITED TALKS
2013.06
A guidance system for off-pump beating heart mitral valve repair
Innovation Centre of Computer Assisted Surgery, Leipzig, Germany
2012.11
Towards Using Synthetic CT and Intro-op TEE images in Guidance of Offpump Beating Heart Interventions
Computational Biomedicine, Imaging, and Modeling Center, Rutgers
University, NJ, USA;
2011.12
Towards Model-Enhanced Real-Time Ultrasound Guided Cardiac
Interventions
Med-X Research Institute, Shanghai Jiao Tong University, Shanghai,
China;
Department of Cardiology, Ruijin Hospital, Shanghai, China
Feng Patrick Li
Octobor 2013
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PUBLICATION & PRESENTATIONS
[1] Feng P. Li, Martin Rajchl, John Moore, Terry M. Peters, Ultrasound based mitral valve
annulus tracking for off-pump beating heart mitral valve repair, SPIE Medical Imaging, 2014
[2] Rajchl M., K. Abhari, J. Stirrat, E. Ukwatta, D. Cantor-Rivera, F. P. Li, T. M. Peters, and J.
A. White, Distribution of guidance models for cardiac resynchronization therapy in the
setting of multi-center clini- cal trials. SPIE Medical Imaging. International Society for Optics
and Photonics, 2014
[3] Feng P. Li, Martin Rajchl, James A. White, Aashish Goela, and Terry M. Peters, Towards
CT Enhanced Ultrasound Guid- ance for Off-pump Beating Heart Mitral Valve Repair. In:
MIAR/AE-CAI 2013.
[4] Marting Rajchl., Jing Yuan, James A.White, Eranga Ukwatta, John Stirrat, Cyrus
Nambakhsh, Feng P. Li, and Terry M. Peters (2013). Interactive Hierarchical Max-Flow
Segmentation of Scar Tissue from Late-Enhancement Cardiac MR Images. IEEE
Transactions on Medical Imaging, 33(1), 159–172
[5] Guotai Wang, Shaoting Zhang, Feng Li, Lixu Gu, A New Segmentation Framework Based
on Sparse Shape Composition in Liver Surgery Planning System, Medical Physics, 2013
(Accepted)
[6] Feng P. Li, Martin Rajchl, James A. White, Aashish Goela, and Terry M. Peters, Generation
of Synthetic 4D Cardiac CT Images for Guidance of Minimally Invasive Beating Heart
Interventions. Information Processing in Computer- Assisted Interventions, 2013
[7] Guotai Wang, Shaoting Zhang, Feng Li, Lixu Gu, Segmentation using Sparse Shape Model
and Minimally Supervised Method in Liver Surgery Planning System, International IEEE
EMBS Conference of the IEEE Engineering in Medicine and Biology Society (Accepted),
2013
[8] Martin Rajchl, Jing Yuan, James A. White, Cyrus M.S. Nambakhsh, Eranga Ukwatta, Feng
Li, John Stirrat, and Terry M. Peters, A Fast Convex Optimization Approach to Segmenting
3D Scar Tissue from Delayed-Enhancement Cardiac MR Images, In: Medical Image
Computing and Computer-Assisted Interventation (MICCAI). Lecture Notes in Computer
Science. Springer Berlin / Heidelberg.2012
[9] Feng P. Li, James A. White, Martin Rajchl, Aashish Goela, and Terry M. Peters, Generation
of Synthetic 4D Cardiac CT Images by Deformation from Cardiac Ultrasound. In: Workshop
on Augmented Environments for Computer-Assisted Interventions (AE-CAI). Lecture Notes
in Computer Science. Springer Berlin / Heidelberg, 2012
[10] Feng Li, Pencilla Lang, Martin Rajchl, Elvis C.S. Chen, Gerard Guiraudon, Terry M. Peters,
Towards Real-time 3D US-CT Registration on the Beating Heart for Guidance of Minimally
Invasive Cardiac Interventions, SPIE Medical Imaging Conference, San Diego, Feb. 4-9,
2012
[11] Pencilla Lang, Martin Rajchl, Feng Li, Terry M. Peters, Towards Model-Enhanced RealTime Ultrasound Guided Cardiac Interventions, International conference on Intelligent
Computation and Bio-Medical Instrumentation, Wuhan, China, Dec. 14-17, 2011
Feng Patrick Li
Octobor 2013
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[12] Feng Li, Pencilla Lang, Martin Rajchl, Elvis C. S. Chen, Gerard Guiraudon, Terry M. Peters,
Towards Real-time 3D US to CT Cardiac Image Registration for Minimally Invasive Cardiac
Intervention Guidance, MICCAI workshop on Augmented Environments for Computer
Assisted Interventions, Toronto, Canada, Sep. 22, 2011
[13] Feng Li, Lixu Gu, Michel A. Audette, Terry M. Peters, A Minimally Supervised
Segmentation Method of Liver, Portal Vein, and Hepatic Vein on 3D Enhanced CT
Abdomen Data, 25th International Congress and Exhibition on Computer Assisted
Radiology and Surgery, Berlin, Germany, Jun. 24-27, 2011
[14] Elvis C.S. Chen, Jonathan McLeod, Pencilla Lang, Feng Li, Terry M. Peters, Automatic
Real-time 3D Ultrasound Calibration Using Single US Volume, 25th International Congress
and Exhibition on Computer Assisted Radiology and Surgery, Berlin, Germany, Jun. 24-27,
2011
[15] Feng Li, Dirk Bartz, Lixu Gu, and Michel A. Audette, An Iterative Classification Method of
2D CT Head Data Based on Statistical and Spatial Information, International Conference on
Pattern Recognition, Tampa, Florida, USA, Dec. 8-11, 2008
RESEARCH INTERESTS & EXPERIENCES
image-guided navigation system, minimally invasive cardiac interventions,
medical imaging, medical image processing
2009-
Robarts Research Institute, The University of Western Ontario
Research Topic: Dynamic Image Fusion for Guidance of Cardiac
Therapies
Comparing to conventional intracardiac therapies, minimally invasive
intracardiac procedures causes less trauma to the patient and can potentially
reduce complications arising from the surgeries, while one problem of minimally
invasive procedure is the limitation of visual access to the surgical target. We are
currently engaged in a project to develop an image-guided navigation system
which aims to integrate both pre-operative and intra-operative imaging and to
provide an intuitive visualization environment as well as broad range of valuable
information for minimally invasive intracardiac procedures. My research interest
is focused on the registration between pre-operative MRI/CT images and intraoperative real-time 2D/3D ultrasound images and the image fusion based on the
registration results. The greatest challenge is the efficiency of the registration,
since multi-modality image registrations are usually time-consuming while intraoperative applications are time-crucial. A Graphics Processing Units (GPU) based
registration method is introduced to accelerate the registration procedure.
2007-2009
Lab of Image Guided Surgery and Therapy,
Shanghai Jiao Tong University
Feng Patrick Li
Octobor 2013
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Master thesis: A Minimally Supervised Classification Method Based on
Statistical and Spatial Information and Its Application in Liver
Segmentation
Hepatectomy and liver transplantation surgeries require detailed information
about the shape and distribution of portal veins and hepatic veins inside liver. In
this thesis I developed a 3D minimally supervised classification method based on
both statistical and spatial information and applied it on enhanced CT abdomen
data in order to segment and visualize liver, portal vein and hepatic vein. The
segmentation results are supposed to provide quantitive information about the
distribution of portal vein and hepatic vein inside liver and support the surgical
planning for hepatectomy and liver transplantation. The segmentation results are
examined by radiologists, compared to manual segmentation results and
considered to be clinically useful.
2006-2008
Technical University of Berlin
Master Thesis: 2D Gaussian-Mixture-Based Bayesian Level Sets for
Head CT Data Classification
The classification of CT head data has many useful applications in the planning
and simulation of ENT and neuro-surgical interventions. Our objective is a
method that yields a clinically useful tissue map, in which air, soft tissues, bone
of both high and low density, as well as possible surgical landmarks are
distinguished. This is a preliminary step to surface and/or volume meshing of
these tissues, or refinement of soft tissue labels if MR is available. In this thesis I
developed an iterative classification method for 2D CT Head data. The method
reduces the chance of misclassification, while still maintaining the tissue
contiguity and retaining the narrow structures. It improves the Bayesian Level
Sets method through greater relevance to tissues in the context of a minimally
supervised classification.