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PhD Tips

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Conferences are less about convincing people; more about confusing people.

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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. David Dagan Feng, A/Prof. Jinman Kim and Clinical Professor Michael Fulham.

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

Google Scholar

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

  • 2019 S2
    Coordinator for INFO5306 - Enterprise Healthcare Information Systems
    School of Computer Science, University of Sydney
  • 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)
  • Reviewer for the International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)
  • 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
21

Xiaohang Fu, Lei Bi, Ashnil Kumar, Michael Fulham, and Jinman Kim, "An Attention-Enhanced Cross-Task Network to Analyse Lung Nodule Attributes in CT Images," in Pattern Recognition (PR), 2022 (accepted). Elsevier PDF

20

L. Bi, M. Fulham, J. Kim, "Hyper-Fusion Network for Semi-Automatic Segmentation of Skin Lesions," in Medical Image Analysis, 2021 (accepted). Elsevier PDF

19

Yige Peng, Lei Bi, Ashnil Kumar, Michael Fulham, Dagan Feng, Jinman Kim, "Predicting distant metastases in soft-tissue sarcomas from PET-CT scans using constrained hierarchical multi-modality feature learning," in Physics in Medicine and Biology, 2021 (accepted). IOPscience PDF

18

Yuyu Guo, Lei Bi, Dongming Wei, Liyun Chen, Zhengbin Zhu, Dagan Feng, Ruiyan Zhang, Qian Wang, Jinman Kim, "Unsupervised Landmark Detection Based Spatiotemporal Motion Estimation for 4D Dynamic Medical Images," in IEEE Transactions on Cybernetics, 2021 (accepted). IEEE Xplore PDF

17

Joyce Zhanzi Wang, Jonathon Lillia, Muhannad Farhan, Lei Bi, Jinman Kim, Joshua Burns, Tegan L. Cheng, "Digital mapping of a manual fabrication method for paediatric ankle–foot orthoses," in Scientific Reports, 2021 (accepted). Scientific Reports PDF

16

Y. Guo, L. Bi, Z. Zhu, D. Feng, R. Zhang, Q. Wang, J. Kim, "Automatic Left Ventricular Cavity Segmentation via Deep Spatial Sequential Network in 4D Computed Tomography," in Computerized Medical Imaging and Graphics (CMIG), 2021 (accepted). Elsevier PDF

15

X. Wu, L. Bi, M. Fulham, D. Feng, L. Zhou, J. Kim, "Unsupervised Brain Tumor Segmentation using a Symmetric-driven Adversarial Network," in Neurocomputing, 2021 (accepted). Elsevier PDF

14

L. Bi, M. Fulham, N. Li, Q. Liu, S. Song, D. Feng, J. Kim, "Recurrent Feature Fusion Learning for Multi-Modality PET-CT Tumor Segmentation," in Computer Methods and Programs in Biomedicine, 2021 (accepted). Elsevier PDF

13

X. Fu, L. Bi, A. Kumar, M. Fulham, J. Kim, "Multimodal Spatial Attention Module for Targeting Multimodal PET-CT Lung Tumor Segmentation," in IEEE Journal of Biomedical and Health Informatics (JBHI), 2021 (accepted). IEEE Xplore PDF

12

M. Meng, X. Yang, L. Bi, J. Kim, S. Xiao, Z. Yu, "High-parallelism Inception-like Spiking Neural Networks for Unsupervised Feature Learning," in Neurocomputing, 2021 (accepted). Elsevier PDF

11

L. Bi, D. Feng, M. Fulham, J. Kim, "Multi-Label Classification of Multi-Modality Skin Lesion via Hyper-Connected Convolutional Neural Network," in Pattern Recognition (PR), vol 107, 2020. Elsevier PDF

10

R. Huang, A. Nedanoski, D. F. Fletcher, N. Singh, J. Schmid, P. M. Young, N. Stow, L. Bi, D. Traini, E. Wong, C. L. Phillips, R. R. Grunstein, J. Kim, "An automated segmentation framework for nasal computational fluid dynamics analysis in computed tomography," in Computers in Biology and Medicine, 2019. Elsevier

9

X. Liu, L. Bi, Y. Xu, D. Feng, J. Kim, X. Xu, "A Robust Deep Learning Method for Choroidal Vessels Segmentation on Swept Source Optical Coherence Tomography Images," in Biomedical Optics Express, , Volume 10, Issue 4, pp 1601-1612, 2019. OSA Open Access

8

Y. Jung, J. Kim, L. Bi, A. Kumar, D. Feng, M. Fulham, "A direct volume rendering visualization approach for serial PET–CT scans that preserves anatomical consistency," in International Journal of Computer Assisted Radiology and Surgery (CARS), 2019. SpringerLink

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), Volume 85, pp 78-89, 2019. Elsevier PDF

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), Volume 34, Issue 6–8, pp 1043 – 1052, 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 (Selected)

# Description
13

Y. Peng, L. Bi, M. Fulham, D. Feng and J. Kim, "Multi-Modality Information Fusion for Radiomics-based Neural Architecture Search," in International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), (Accepted) 2020. SpringerLink

12

X. Li, L. Bi, J. Kim, T. Li, B. Sheng and D. Feng, "Malocclusion Treatment Planning via PointNet based Spatial Transformation Network," in International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), (Accepted) 2020. SpringerLink

11

Y. Guo, L. Bi, E. Ahn, D. Feng, Q. Wang, and J. Kim, "A Spatiotemporal Volumetric Interpolation Network for 4D Dynamic Medical Image," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (accepted), 2020. PDF

10

Y. Guo, L. Bi, A. Kumar, Y. Gao, R. Zhang, J. Kim, Q. Wang and D. Feng, "Deep Local-Global Refinement Network for Stent Analysis in IVOCT Images," in International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp539-546, 2019. SpringerLink PDF

9

L. Bi, D. Feng, M. Fulham, and J. Kim, "Improving Skin Lesion Segmentation via Stacked Adversarial Learning," in International Symposium on Biomedical Imaging: From Nano to Macro (ISBI), 2019. IEEE Xplore PDF

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

Book Chapters

# Description
1

A. Kumar, L. Bi, J. Kim, D. Feng, "Machine learning in medical imaging," in Biomedical Information Technology, Academic Press, 167-196, 2020. Elsevier Book Chapter


Photos