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About

I'm a research fellow of the Australia Research Council Training Centre in Innovative BioEngineering, a research coordinator (USYD) with the Shanghai Jiao Tong University – University of Sydney (SJTU-USYD) Joint Research Alliance and a member of the Biomedical Multimedia Information Technology (BMIT) research group, the University of Sydney. I work closely with clinicians from hospitals in Australia and China, including the Royal Prince Alfred, Westmead, Ruijin and Renji Hospital. During my PhD, I was supervised by Prof. Dagan Feng, A/Prof. Jinman Kim and Clinical Professor Michael Fulham.

My current research interests include biomedical image analysis and disease mapping ( ).

E-mail: lei [DOT] bi [AT] sydney [DOT] edu [DOT] au

Year Degree
2014 - 2018 Doctor of Philosophy
BMIT Research Group, School of Information Technologies, University of Sydney
2012 - 2013 Master of Philosophy
BMIT Research Group, School of Information Technologies, University of Sydney
2011 - 2012 Master of Information Technology
School of Information Technologies, University of Sydney
2008 - 2010 Bachelor of Computer Science
Faculty of Science, Macquarie University

Career

Employment

  • 2016 S2
    Teaching Assistant for INFO5992 - Understanding Information Technology Innovations
    School of Information Technologies, University of Sydney
  • 2014 S2, 2015 S2, 2016 S2
    Teaching Assistant for INFO5306 - Enterprise Healthcare Information Systems
    School of Information Technologies, University of Sydney
  • 2012 S2, 2013 S1, 2013 S2, 2014 S1, 2015 S1
    Teaching Assistant for COMP5206 - Introduction to Information Systems
    School of Information Technologies, University of Sydney
  • 2012 - Present
    Research Assistant
    BMIT Research Group, School of Information Technologies, University of Sydney
  • 2010 - 2012
    Quality Assurance Analyst
    Altec Lansing Pty Limited, North Sydney
  • 2009 - 2010
    Quality Assurance Analyst
    Avega Systems Pty Limited, North Sydney
  • 2009
    Lab Officer
    Faculty of Science, Macquarie University
  • 2015
    MICCAI-CMMI Best Paper Award
    Adaptive Supervoxel Patch-based Region Classification in Whole-Body PET-CT
    L. Bi, J. Kim, A. Kumar, D. Feng, M. Fulham
  • 2013 - Present
    Australian Postgraduate Award (APA)
    Government of Australia
  • 2012
    CARS 2012 EuroPACS Best Poster Award
    for An image retrieval interface for volumetric multi-modal medical data:
    A. Kumar, J. Kim, L. Bi, D. Feng
    26th International Congress on Computer Assisted Radiology and Surgery
  • 2011 - 2012
    Summer Research Scholarship
    BMIT,School of Information Technologies, University of Sydney
  • 2011
    Information Technology Project Highest Mark Award
    School of Information Technologies, University of Sydney
  • 2009
    Microsoft Certified Technology Specialist
    Windows Server Network Infrastructure: Configuration
    Microsoft Windows: Configuration
  • 2008
    Highest Mark Award: COMP115 Introduction to Computer Science
    Highest Mark Award: MATH130 Mathematics 1E
    Sydney Institute of Business and Technology, Macquarie University

Achievements

Professional Services / Activities

  • Reviewer for IEEE Transactions on Medical Imaging (IEEE TMI)
  • Reviewer for IEEE Transactions on Cybernetics (IEEE TCYB)
  • Reviewer for IEEE Journal of Biomedical and Health Informatics (IEEE JBHI)
  • Reviewer for Computer Methods and Programs in Biomedicine (CMPB) journal
  • Reviewer for The Visual Computer Journal (Springer)
  • 2015, 2016, 2017, 2018
    Reviewer for The IEEE International Symposium on Biomedical Imaging (ISBI)
  • 2014
    Local Organising Committee Member for The 31st Computer Graphics International (CGI 2014)
  • 2013
    Local Organising Committee Member for The 6th IEEE Pacific Visualization (PacificVis 2013)

Publications

Journal Papers

# Description
7

L. Bi, J. Kim, E. Ahn, A. Kumar, D. Feng and M. Fulham, "Step-wise Integration of Deep Class-specific Learning for Dermoscopic Image Segmentation," in Pattern Recognition (PR), 2018.

6

L. Bi, D. Feng and J. Kim, "Dual-Path Adversarial Learning for Fully Convolutional Network (FCN)-Based Medical Image Segmentation," in The Visual Computer Journal (TVCJ), 2018. Springer PDF

5

L. Bi, J. Kim, E. Ahn, A. Kumar, M. Fulham and D. Feng, "Dermoscopic Image Segmentation via Multi-Stage Fully Convolutional Networks," in IEEE Transactions on Biomedical Engineering (TBME), Volume 64, Issue 9, pp 2065 - 2074, 2017. IEEE Xplore PDF

4

L. Bi, J. Kim, A. Kumar, M. Fulham and D. Feng, "Stacked Fully Convolutional Networks with Multi-Channel Learning: Application to Medical Image Segmentation," in The Visual Computer Journal (TVCJ), Volume 33, Issue 6-8, pp 1061-1071, 2017. Springer PDF

3

E. Ahn, J. Kim, L. Bi, A. Kumar, C. Li, M. Fulham and D. Feng, "Saliency -based Lesion Segmentation via Background Detection in Dermoscopic Images," in IEEE Journal of Biomedical and Health Informatics (JBHI), Volume 21, Issue 6, pp 1685 - 1693, 2017. IEEE Xplore PDF

2

L. Bi, J. Kim, A. Kumar, L. Wen, D. Feng and M. Fulham, "Automatic Detection and Classification of Regions of FDG Uptake in Whole-Body PET-CT Lymphoma Studies," in Computerized Medical Imaging and Graphics (CMIG), Volume 60, pp 3-10, 2017. Elsevier PDF

1

A. Kumar, J. Kim, L. Bi, M. Fulham, and D. Feng, "Designing user interfaces to enhance human interpretation of medical content-based image retrieval: application to PET-CT images," in International Journal of Computer Assisted Radiology and Surgery (CARS), Volume 8, Issue 6, pp 1003-1014, 2013. SpringerLink

Conference Papers

# Description
8

L. Bi, J. Kim, T. Su, M. Fulham, D. Feng, and G. Ning, "Adrenal Lesions Detection on Low-Contrast CT Images using Fully Convolutional Networks with Multi-Scale Integration," in International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), pp895-898, 2017. IEEE Xplore PDF

7

L. Bi, J. Kim, E. Ahn, D. Feng, and M. Fulham, "Semi-Automatic Skin Lesion Segmentation via Fully Convolutional Networks," in International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), pp561-564, 2017. IEEE Xplore PDF

6

L. Bi, J. Kim, E. Ahn, D. Feng, and M. Fulham, "Automated Skin Lesion Segmentation via Image-wise Supervised Learning and Multi-scale Superpixel Based Cellular Automata," in International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), pp1059-1062, 2016. IEEE Xplore PDF Code Available

5

L. Bi, J. Kim, E. Ahn, D. Feng, and M. Fulham, "Automatic Melanoma Detection via Multi-scale Lesion-biased Representation and Joint Reverse Classification," in International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), pp1055-1058, 2016. IEEE Xplore PDF

4

R. Huang, A. Li, L. Bi, C. Li, P. Young, J. Kim and D. Feng, "A Locally Constrained Statistical Shape Model for Robust Nasal Cavity Segmentation in Computed Tomography," in International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), pp1334-1337, 2016. IEEE Xplore PDF

3

L. Bi, J. Kim, L. Wen, D. Feng, and M. Fulham, "Automated Thresholded Region Classification Using A Robust Feature Selection Method For PET-CT," in International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), pp1435-1438, 2015. IEEE Xplore PDF

2

L. Bi, J. Kim, A. Kumar, D. Feng, and M. Fulham, "Adaptive Supervoxel Patch-based Region Classification in Whole-Body PET-CT," in Medical Image Computing and Computer Assisted Intervention (MICCAI) - Computational Methods for Molecular Imaging (CMMI), 2015. SpringerLink PDF Best Paper Award

1

L. Bi, J. Kim, D. Feng, and M. Fulham, "Multi-stage Thresholded Region Classification for Whole-Body PET-CT Lymphoma Studies," in The 17th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp569-576, 2014. SpringerLink PDF


Links

University of Sydney

The University of Sydney is a public university founded in 1850. Throughout its history, Sydney consistently ranks amongst the top universities in Australia and Oceania.

BMIT

The Biomedical & Multimedia Information Technology (BMIT) Research Group is one of leading research groups in the biomedical research area.

Dr. Jinman Kim

Dr. Jinman Kim is a ARC postdoc research fellow and has many years research experiences on biomedical image processing and visualization.

CGI 2014

The 31st CGI will be hosted at beautiful city of Sydney on June 10-13, 2014. Sydney is known for its harbour lifestyle, fantastic beaches and good weather - all contributing to a relaxed environment that permeates the city and its visitors.

BMET

BMET covers broad biomedical engineering and technology fields such as image processing and data management, image visualisation and analysis, bioinformatics and data mining, medical devices and networking, biomaterials and regenerative tissue engineering.

PacificVis 2013

The 6th PacificVis (Pacific Visualization) will be held in Sydney, Australia during February 26 to March 1, 2013. As part of PacificVis, workshop/tutorial sessions will be held on February 26, with the Symposium starting from February 27.

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