News
1. Zhou is
moving to University of Sydney.
Personal website is here.
2. We are
organizing a special issue on “High Performance Computing in Bio-medical Informatics” (HPC-BMI) with Neuroinformatics (Springer). The online Call-for-Paper is available here. Paper submission
period is May 1-31, 2017.
3. Our
organising committee has successfully bid MICCAI 2019 in Hong Kong (General
Chairs: Prof Dinggang Shen @ UNC-CH and Prof Tianming Liu @ UGA).
4.
We are organizing a special issue
“Machine Learning in Medical Imaging” with Pattern Recognition
(Elsevier). The online Call-for-Paper
is available here. The
submission is due on January 31, 2016, through
the website
here. Please select “SI:MLMI” for “Article
Type” during the submission procedure.
5.
Zhou received
the early career award (DECRA 2016-2018) from Australian Research Council.
6.
Zhou is in the list of MICCAI’15 Best Reviewers Runner-ups (14 in total over
700 Peer Reviewers).
7.
Update: the workshop MICCAI-MLMI’15 has been completed successfully. This
year, we again attracted above 140 registrants. The proceedings are available
online here.
We are organizing the 6th international
workshop on Machine Learning in Medical Imaging (MLMI 2015), held together with MICCAI 2015,
in Munich, Germany. MLMI focuses on advancing the cutting-edge machine
learning techniques and their use in medical imaging. The last workshop, MLMI
2014 held in Boston USA, attracted around 100 attendees, and the proceedings
could be found here.
8.
Zhou gave an invited talk on BrainKDD2015, hosted by ACM SIGKDD
in Sydney in 2015.
Related Publications
(Note: ARC
ERA2010 Ranking A*/A is highlighted in yellow)
|
2019
|
|
J27
|
B. Yu, L.
Zhou*, L. Wang*, Y. Shi, J. Fripp, and P. Bourgeat, "Ea-GANs:
Edge-aware Generative Adversarial Networks for Cross-modality MR Image
Synthesis", IEEE Transactions on Medical Imaging (IEEE T-MI), 2019
(*co-corresponding authors, accepted in January, 2019)
|
|
C38
|
R. Su,
W. Ouyang, L. Zhou, and D. Xu, "Improving Action
Localization by Progressive Cross-stream Cooperation", IEEE
Computer Society Conference on Computer Vision and Pattern Recognition
(CVPR), Long Beach, USA, 2019
|
|
2018
|
|
J26
|
Y. Wang,
L. Zhou*, B. Yu, L. Wang, C. Zu, D.S. Lalush,
W. Lin, X. Wu, J. Zhou, and D. Shen* ,
"3D Auto-context-based Locality Adaptive Multi-modality GANs for PET
Synthesis ", IEEE Transactions on Medical Imaging (IEEE T-MI),
(*co-corresponding authors, accepted in November 2018)
|
|
J25
|
Z. Gao,
L. Wang, L. Zhou, "A Probabilistic Approach to Cross-region
Matching based Image Retrieval", IEEE Transactions on Image Processing
(IEEE T-IP), 2018 (accepted in September, 2018)
|
|
J24
|
Y. Wang,
B. Yu, L. Wang, C. Zu, D.S. Lalush, W. Lin, X.
Wu, J. Zhou, D. Shen*, and L. Zhou*, "3D Conditional
Generative Adversarial Networks for High-quality PET Image Estimation at
Low Dose", Neuroimage, 2018 (*co-corresponding authors)
|
|
C37
|
M. Engin, L. Wang, L. Zhou, and X. Liu, "DeepKSPD: Learning Kernel-matrix-based SPD
Representation for Fine-grained Image Recognition", European
Conference on Computer Vision (ECCV), Munich, Germany, 2018
|
|
C36
|
Y. Wang,
L. Zhou*, L. Wang, B. Yu, C. Zu, D.S. Lalush,
W. Lin, X. Wu, J. Zhou, and D. Shen*, "Locality
Adaptive Multi-modality GANs for High-quality PET Image Synthesis", International
Conference on Medical Image Computing And Computer Assisted Intervention
(MICCAI), Granada, Spain, 2018 (*co-corresponding authors)
|
|
C35
|
Y. Zhao,
L. Wang, L. Zhou, Y. Shi, and Y. Gao, "Modeling
Diffusion Process by Deep Neural Networks for Image Retrieval", British Machine Vision Conference (BMVC),
Newcastle, UK, 2018
(spotlight presentation)
|
|
C34
|
C. Zu,
Y. Wang, L. Zhou, L. Wang, and D. Zhang, “Multi-modality Feature
Selection with Adaptive Similarity Learning for Classification of
Alzheimer's Disease”, IEEE International Symposium on Biomedical
Imaging (ISBI), Washington DC, USA, 2018 (oral)
|
|
C33
|
B. Yu, L.
Zhou*, L. Wang, J. Fripp, and P. Bourgeat, “3D cGAN based
Cross-modality MR Image Synthesis for Brain Tumor
Segmentation”, IEEE International Symposium on Biomedical Imaging
(ISBI), Washington DC, USA, 2018 (corresponding author, oral)
|
|
C32
|
Y. Wang,
B. Yu, L. Wang, C. Zu, Y. Luo, X. Wu, J. Zhou, and L. Zhou*, “Tumor Segmentation via Multi-modality Joint
Dictionary Learning”, IEEE International Symposium on Biomedical
Imaging (ISBI), Washington DC, USA, 2018 (corresponding author)
|
|
C31
|
P. Tian,
L. Qi, Y. Shi, L. Zhou, Y. Gao, and D. Shen, “A Novel
Image-specific Transfer Approach for Prostate Segmentation in MR Images”,
IEEE International Conference on Acoustics, Speech, and Signal Processing
(ICASSP), Alberta, Canada, 2018
|
|
C30
|
Z.
Zhang, L. Wang, Y. Wang, L. Zhou, J. Zhang and F. Chen, “Instance
Image Retrieval by Aggregating Sample-based Discriminative Characteristics”,
ACM International Conference on Multimedia Retrieval (ICMR), Yokohama,
Japan, 2018
|
|
C29
|
J. Wu, L.
Zhou, C. Cai, J. Shen, and S.K. Lau, “Data Fusion for MaaS: Opportunities and Challenges”, IEEE 22nd
International Conference on Computer Supported Cooperative Work in Design
(CSCWD), Nanjing, China, 2018
|
|
2017
|
|
J23
|
H. An, L.
Zhou, Y. Yu, H. Fan, F. Fan, S. Tan, Z. Wang, Z B, J. Shi, F. Yang, X.
Zhang, Y. Tan, X. Huang, Serum NCAM levels and
cognitive deficits in first episode schizophrenia patients versus health
controls, Schizophrenia Research,
2017 (online in June, 2017)
|
|
J22
|
W.
Li, Y. Gao, L.
Wang, L. Zhou, J. Huo,
and Y. Shi, OPML: A One-Pass
Closed-Form Solution for Online Metric Learning, Pattern Recognition (PR), 2017 accepted
|
|
J21
|
H. Ni, J. Qin, L.
Zhou, Z. Zhao, J. Wang, and F. Hou, Network Analysis in Detection of Early-stage Mild Cognitive
Impairment, Physica A:
Statistical Mechanics and its Applications, 2017 accepted
|
|
C28
|
L. Zhou,
L. Wang, J. Zhang, Y. Shi and Y. Gao, Revisiting Distance Metric Learning for SPD
Matrix based Visual Representation, IEEE
Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Hawaii, USA, 2017
|
|
C27
|
Z. Gao,
L. Wang, L. Zhou, and M. Yang, Infomax Principle Based Pooling of Deep
Convolutional Activations for Image Retrieval, IEEE International Conference on Multimedia and Expo (ICME), Hong Kong, 2017 (Finalist of the World's FIRST 10K Best Paper Award)
|
2016
|
J20
|
L. Zhou,
L. Wang, L. Liu, P. Ogunbona, and D. Shen, Learning Discriminative Bayesian
Networks from High-dimensional Continuous Neuroimaging Data, IEEE Transactions on Pattern Analysis
and Machine Intelligence (T-PAMI), accepted. [Appendix]
|
|
J19
|
L. Wang,
L. Liu, and L. Zhou, A Graph-embedding Approach to
Hierarchical Visual Word Mergence, IEEE
Transactions on Neural Networks and Learning Systems (T-NNLS) 2016, accepted.
|
|
J18
|
J. Zhang, L. Zhou, and L. Wang, Subject-adaptive
Integration of Multiple SICE Brain Networks with Different Sparsity, Pattern Recognition (PR), 2016, accepted.
|
|
J17
|
Z. Gao, L. Wang, L. Zhou
and J. Zhang, HEp-2
Cell Image Classification with Deep Convolutional Neural Networks, IEEE Journal of Biomedical and Health
Informatics (IEEE JBHI, originally IEEE T-ITB), 2016 (accepted in Jan 2016).
|
|
C26
|
Y. Zhao, L. Wang, I. Comor, Z. Gao, W. Zhang, and L. Zhou, Semi-supervised
Weight Learning for the Spatial Search Method in ConvNet-based
Image Retrieval,The International Conference on Digital Image
Computing Techniques and Applications (DICTA), Gold Coast, Australia,
2016
|
|
C25
|
I. Comor, Y. Zhao, Z. Gao, L. Zhou, and L. Wang, Image Descriptors from ConvNets:
Comparing Global Pooling Methods for Image Retrieval, The International Conference on Digital Image Computing Techniques and Applications
(DICTA), Gold Coast, Australia, 2016
|
|
2015
|
|
|
B2
|
L. Zhou,
L. Wang, Q. Wang, and Y. Shi (Eds.), Machine Learning in Medical Imaging
– 6th international
workshop, MLMI2015, Held in Conjunction
with MICCAI 2015 in Munich, Germany, Proceedings, Springer
(ISBN: 978-3-319-24888-2), 2015
|
|
J16
|
H. Ni, L. Zhou, X. Ning, and L. Wang*, Exploring
Multifractal-based Features for Mild Alzheimer’s Disease Classification, Magnetic
Resonance in Medicine (MRM), 2015 (accepted in June 2015)
|
|
J15
|
J. Zhang,
L. Wang, L. Zhou, and W. Li, Learning Discriminative Stein Kernel
for SPD Matrices and Its Applications, IEEE Transactions on Neural Networks and Learning Systems (T-NNLS), 2015 (accepted in May
2015)
|
|
J14
|
J. Zhang,
L. Zhou, L. Wang, and W. Li, Functional Brain
Network Classification with Compact Representation of SICE Matrices, IEEE Transactions on Biomedical
Engineering (T-BME), 2015 (accepted in Jan 2015)
|
|
|
|
|
J13
|
H. Ni, L. Zhou, P. Zeng, X. Huang, H. Liu,
X. Ning, Multifractal Analysis of White Matter Structural
Changes on 3D Magnetic Resonance Imaging between Normal Ageing
and Early Alzheimer’s Disease, Chinese Physics B (English Edition),
2015 (accepted in March 2015, SCI-indexed, IF 1.39)
|
|
C24
|
L. Wang, J. Zhang, L. Zhou, C. Tang, and W. Li, Beyond Covariance: Feature
Representation with Nonlinear Kernel Matrices, International Conference on Computer Vision (ICCV), Santiago,
Chile, 2015
|
|
2014
|
|
|
B1
|
G. Wu, D.
Zhang, and L. Zhou (Eds.), Machine Learning in Medical Imaging
– 5th international workshop,
MLMI2014, Held in Conjunction
with MICCAI 2014 in Boston, USA, Proceedings, Springer (ISBN: 978-3-319-10580-2),
2014
|
|
J12
|
X. Liu, L. Zhou, L. Wang, J. Zhang, J. Yin,
and D. Shen, An
Efficient Radius-incorporated MKL Algorithm for Alzheimer’s Disease
Prediction, Pattern
Recognition (PR), 2014
(accepted in Dec 2014)
|
|
C23
|
L. Zhou,
L. Wang, and P. Ogunbona, Discriminative Sparse Inverse Covariance Matrix: Application in
Brain Functional Network Classification, IEEE Computer Society Conference on Computer Vision and Pattern
Recognition (CVPR), Ohio, USA, 2014
|
|
|
|
|
C22
|
L. Zhou,
L. Wang, L. Liu, P. Ogunbona, and D. Shen, Max-margin Based Learning for
Discriminative Bayesian Network from Neuroimaging Data, International Conference on Medical Image
Computing And Computer Assisted Intervention
(MICCAI), Boston, USA, 2014
|
|
C21
|
J. Zhang,
L. Zhou, L. Wang, and W. Li, Exploring Compact Representation of
SICE Matrices for Functional Brain Network Classification, MICCAI Workshop on Machine Learning in
Medical Imaging (MLMI), Boston, USA, 2014
|
|
C20
|
Z. Gao, J. Zhang, L. Zhou and L. Wang, HEp-2 Cell Image Classification with
Convolutional Neural Networks, Contest
on Pattern Recognition Techniques for Indirect Immunofluorescence Images
Analysis in International Conference on Pattern Recognition (ICPR),
Sweden, 2014 (invited paper)
|
|
C19
|
Y. Zhao, Z. Gao, L. Wang and L.
Zhou, Experimental Study of Unsupervised Feature
Learning for HEp-2 Cell Images Clustering, The International Conference on
Digital Image Computing: Techniques and Applications (DICTA), Wollongong, Australia, 2014
|
|
CA6
|
V. Doré, P. Bourgeat, L. Zhou, J. Fripp,
R. Martins, L. Macaulay, D. Ames, C. L. Masters, B. Brown, C. C. Rowe, O. Salvado, and V. L. Villemagne.
Automated Reporting of Amyloid PET
Quantification on Brain Surface through a Web Interface, In Alzheimer's Association International
Conference in Alzheimer's Disease (AAIC), Copenhagen, Denmark, & Alzheimer’s and Dementia: journal of
Alzheimer’s Association, 2014
|
|
BC3
|
L. Zhou,
L. Wang, L. Liu, P. Ogunbona and D. Shen, Support
Vector Machines for Neuroimage Analysis: Interpretation from Discrimination.
Support Vector Machines Applications, Springer (ISBN: 978-3-319-02300-7), 2013
|
|
BC2
|
L.
Wang, L. Liu, L. Zhou and K.L. Chan, Application of SVMs to the
Bag-of-features Model – A Kernel Perspective. Support Vector
Machines Applications, Springer (ISBN: 978-3-319-02300-7), 2013
|
|
J11
|
L. Wang, L.
Zhou, C. Shen, L. Liu and H. Liu, A
Hierarchical Word-merging Algorithm with Class Separability Measure, IEEE Transactions on Pattern Analysis
and Machine Intelligence (T-PAMI), 2013 (accepted in August,
2013)
|
|
J10
|
L. Zhou,
O. Salvado, V. Dore, P. Bourgeat,
P. Raniga, S. L. Macaulay, D. Ames, C. L.
Masters, K. A. Ellis, V. L. Villemagne, C. C.
Rowe, and J. Fripp, MR-less Surface-based
Amyloid Assessment based on 11C PiB
PET, PLoS One, 2013 (accepted in Novermber, 2013)
|
|
J9
|
V. Dore, V. L. Villemagne,
P. Bourgeat, J. Fripp,
O. Acosta, G. Chetelat, L. Zhou, R.
Martins, K. Ellis, C. L. Masters, D. Ames, , O. Salvado, and C. C. Rowe. Cross-sectional and
Longitudinal Analysis of the Relationship between Aβ Deposition,
Cortical Thickness and Memory in Cognitively Unimpaired Individuals and
Alzheimer’s Disease, JAMA Neurology 2013;70(7):903-911
|
|
J8
|
F. Liu, L. Zhou, C. Shen, J. Yin. Multiple Kernel Learning in the Primal
for Multi-modal Alzheimer’s Disease Classification, IEEE Journal on Biomedical and Health
Informatics (originally IEEE Trans
on Information Technology in Biomedicine), 2013
|
|
C18
|
L. Zhou, L. Wang, L. Liu, P. Ogunbona,
and D. Shen, Discriminative Brain
Effective Connectivity Analysis for Alzheimers
Disease: A Kernel Learning Approach upon Sparse Gaussian Bayesian Network,
IEEE Computer Society Conference on
Computer Vision and Pattern Recognition (CVPR), Oregon, USA, 2013
|
|
C17
|
L. Wang, J. Zhang, L. Zhou, and W. Li, A
Fast Approximate AIB Algorithm for Distributional Word Clustering, In IEEE Computer Society Conference on Computer
Vision and Pattern Recognition (CVPR), Oregon, USA, 2013
|
|
C16
|
J. Zhang, L. Wang, L. Liu, L. Zhou, W. Li. Accelerating
the Divisive Information-Theoretic Clustering of Visual Words, In International Conference on Digital
Image Computing Techniques and Applications (DICTA), Tasmania,
Australia, 2013
|
|
CA5
|
V. Dore, P. Bourgeat, L. Zhou, J. Fripp,
R. Martins, L. Macaulay, C. Masters, D. Ames, K.A. Ellis, C. Rowe, O. Salvado, and V. Villemagne. MR-less
Cortical Surface-projection of PET Scans with 11C and 18F Labeled Radiotracers, In Alzheimer's Association International Conference in Alzheimer's
Disease (AAIC), Boston, USA & Alzheimer’s
and Dementia: journal of Alzheimer’s Association, 2013
|
|
2012
|
|
|
|
|
C15
|
L. Zhou,
O. Salvado, V. Dore, P. Bourgeat,
P. Raniga, V. L. Villemagne,
C. C. Rowe, and J. Fripp, MR-less Surface-based Amyloid Estimation by Subject-specific Atlas
Selection and Bayesian Fusion, In
Proc. International Conference on Medical Image Computing And Computer Assisted Intervention (MICCAI), France,
October 2012
|
|
C14
|
P. Bourgeat, P. Raniga, V. Dore,
L. Zhou, S.L. Macaulay, R. Martins, C. Masters, D. Ames, K. A. Ellis,
V. Villemagne, C. Rowe, O. Salvado,
and J. Fripp. Manifold Driven MR-less PiB SUVR Normalisation, In
MICCAI 2012 Workshop on Novel Imaging Biomarkers for Alzheimer's
Disease and Related Disorders (NIBAD'12), Nice, France, October
2012.
|
|
CA4
|
L. Zhou, V. Dore, J. Fripp, P. Bourgeat ,P.
Raniga, R. Martins, L. Macaulay, C. Masters, D.
Ames, K. A. Ellis, V. Villemagne, C. Rowe, O. Salvado, and AIBL research group. MRI-independent Automated Surface-projection of Amyloid Imaging
Scans, In Alzheimer's Association
International Conference in Alzheimer's Disease (AAIC), Canada, & Alzheimer’s and Dementia: journal of
Alzheimer’s Association, 2012
|
|
CA3
|
P. Bourgeat, J. Fripp, P. Raniga, V. Dore, L. Zhou, R. Martins, L. Macaulay,
C. Masters, D. Ames, K.A. Ellis, V. Villemagne,
C. Rowe, O. Salvado, and AIBL research group, Longitudinal Modeling
of Joint PiB/MRI Changes in Alzheimer’s Disease,
In Alzheimer's Association
International Conference in Alzheimer's Disease 2012, Vancouver (AAIC),
Canada, & Alzheimer’s and
Dementia: journal of Alzheimer’s Association, 2012
|
|
|
CA2
|
P. Bourgeat, O. Salvado, P. Raniga, V. Dore, L. Zhou, R. Martins, L. Macaulay,
C. Masters, D. Ames, K. A. Ellis, V. Villemagne,
C. Rowe,J. Fripp, and
AIBL research group, Classification
of Alzheimer’s subject based on PiB-MR Manifold
learning, In Alzheimer's Association International Conference in Alzheimer's
Disease (AAIC), Canada, & Alzheimer’s
and Dementia: journal of Alzheimer’s Association, 2012.
|
|
|
CA1
|
V. Dore, J. Fripp, P. Bourgeat, O. Acosta,
L. Zhou, P. Raniga, R. Martins, L. Macaulay,
K. Ellis, C. Masters, D. Ames, V. Villemagne, C.
Rowe, O. Salvado and AIBL research group, Longitudinal
Analysis of Cortical Thickness in PiB+ and PiB- Healthy Elderly Controls, In Alzheimer's
Association International Conference in Alzheimer's Disease (AAIC)
Canada, & Alzheimer’s and
Dementia: journal of Alzheimer’s Association, 2012.
|
|
|
2011
|
|
|
BC1
|
C.Y. Wee*, D. Zhang*, L. Zhou*, P.T. Yap, and D. Shen. Machine Learning Techniques for AD/MCI
Diagnosis and Prognosis (invited book chapter). Machine Learning in Healthcare Informatics, Springer, 2011. (*
equally contribute)
|
|
|
J7
|
L. Zhou, Y.
Wang, Y. Li, P.T. Yap, and D. Shen, Hierarchical Anatomical Brain
Networks for MCI Prediction: Revisiting Volumetric Measures, accepted by PLoS
One, 2011.
|
.
|
|
J6
|
D. Zhang, Y. Wang, L. Zhou,
H. Yuan, and D. Shen, Multimodal Classification of Alzheimer's Disease
and Mild Cognitive Impairment, accepted by NeuroImage,
2011.
|
|
|
J5
|
Y. Li, Y. Wang, G. Wu, F. Shi, L.
Zhou, W. Lin, and D. Shen, Discriminant Analysis of Longitudinal
Cortical Thickness Changes in Alzheimer's Disease Using Dynamic and Network
Features, accepted by Neurobiology of Aging, 2011.
|
|
|
C13
|
L. Zhou, Y.
Wang, Y. Li, P.T. Yap, and D. Shen, Hierarchical Anatomical Brain
Networks for MCI Prediction by Partial Least Square Analysis, In
IEEE Computer Society Conference on Computer Vision and Pattern Recognition
(CVPR 11), Colorado Springs, USA, June 21-23, 2011.
|
|
|
C12
|
L. Zhou, S.
Liao, W. Li, and D. Shen, Learning-based Prostate Localization for Image
Guided Radiation Therapy (invited paper), In IEEE International
Symposium on Biomedical Imaging (ISBI), Chicago, USA, March 30 - April 2, 2011.
|
|
|
C11
|
L.
Zhou and O. Salvado,
A Comparison Study of Ellipsoid Fitting for Pose Normalization of
Hippocampal Shapes, In Proceedings
of International Conference on Digital Image Computing: Techniques and
Applications (DICTA), Brisbane, Australia, December 2011.
|
|
|
|
|
|
2010
|
|
|
|
|
|
|
J4
|
L. Zhou, L.
Wang, and C. Shen, Feature Selection with Redundancy-constrained Class
Separability, IEEE Transactions on Neural Networks 21(5):853-858,
2010.
|
|
|
C10
|
L. Zhou, L.
Wang, C. Shen, and N. Barnes, Hippocampal Shape Classification Using
Redundancy Constrained Feature Selection, In International
Conference on Medical Image Computing And Computer
Assisted Intervention (MICCAI) 2010: 266-273 2010. (MICCAI Travel Award)
|
|
|
2009
|
|
|
|
|
|
|
J3
|
L. Zhou, R.
Hartley, L. Wang, P. Lieby and N. Barnes, Identifying
Anatomical Shape Difference by Regularized Discriminative Direction, IEEE
Transactions on Medical Imaging 28(6): 937-950 2009.
|
|
|
J2
|
L. Zhou, P. Lieby, N. Barnes, C. Reglade-Meslin,
J. Walker, N. Cherbuin, and R. Hartley, Hippocampal
Shape Analysis for Alzheimer’s Disease Using an Efficient Hypothesis Test
and Regularized Discriminative Deformation, Hippocampus, 19(6), June
2009, pp533-540, 2009. (Impact
Factor: 5.176)
|
|
|
C9
|
Q. Shi, L. Zhou, L.
Cheng, and D. Schuurmans, Discriminative Maximum Margin Image Object
Categorization with Exact Inference,, International Conference
on Image and Graphics, September, Xi'An China,
2009.
|
|
|
2008
|
|
|
|
|
|
|
C8
|
L. Zhou, R.
Hartley, L. Wang, P. Lieby, and N. Barnes Regularized
Discriminative Direction for Shape Difference Analysis,, In International Conference
on Medical Image Computing And Computer Assisted Intervention (MICCAI)
2008: 628-635, 2008.
|
|
|
C7
|
L. Wang, L. Zhou, and C.
Shen, A Fast Algorithm for Creating a Compact and Discriminative Visual
Codebook, European Conference on Computer Vision (ECCV) 2008:
719-732 2008.
|
|
|
J1
|
L. Wang, K.L. Chan, P. Xue, and L. Zhou, A Kernel-Induced Space
Selection Approach to Model Selection in KLDA, IEEE Transactions on
Neural Networks 19(12): 2116-2131 2008.
|
|
|
2007
|
|
|
|
|
|
|
C6
|
L. Zhou, R.
Hartley, P. Lieby, N. Barnes, K. Anstey, N. Cherbuin, and P. Sachdev, A Study of Hippocampal
Shape Difference Between Genders by Efficient Hypothesis Test and
Discriminative Deformation,,
In International Conference on Medical Image Computing And Computer
Assisted Intervention (MICCAI) 2007: 375-383, 2007.
|
|
|
Before 2006
|
|
|
|
|
|
|
|
|
|
C5
|
L. Zhou, Y.
Wang, C. Goh,, R.A. Kockro
and L. Serra, Stereoscopic Visualization and Editing of Automatic
Abdominal Aortic Aneurysms (AAA) Measurements for Stent Graft Planning,,
In Proceedings of SPIE’s Electronic Imaging, USA, January 2006, pp57-65,,
2006
|
|
|
C4
|
R.A. Kockro,
X. Liang, C. Goh, L. Zhou, C. Zhu, TT Yeo, and L. Serra, DexRay: An Augmented Reality Surgical Navigation System, In
Conference of European Association of Neurosurgical Societies (EANS),
Portugal, September,
2003.
|
|
|
C3
|
L. Zhou, I. Atmosukarto, W.K. Leow, and
Z. Huang, Reconstruting Surface
Discontinuities by Intersecting Tangent Planes of Advancing Mesh Frontiers,
In Proc. Computer Graphics International (CGI), UK, July 2002, pp183-199,, 2002.
|
|
|
C2
|
I. Atmosukarto,
L. Zhou, W.K. Leow, and Z. Huang, Polygonizing Nonuniformly Distributed 3D
Points by Advancing Mesh Frontier, In Proc. Computer Graphics International
(CGI), Hong Kong, July 2001, pp175-182,, 2001.
|
|
|
C1
|
W.K. Leow,
Z. Huang, L. Zhou, I. Atmosukarto, and Y.
Zhang, Acquiring 3D Models from Images for Multimedia Systems, In
Proc. Multimedia Modeling (MMM), Japan, November
2000, pp439-449,,
2000.
|
|
|
|
[Ongoing]
Biting Yu: PhD, University of Wollongong (Primary Supervisor)
Topic: “Deep Learning Techniques
for Medical Image Analysis”
Zhimin Gao: PhD, University of Wollongong (Supervision
Panel)
Topic:“Developing Advanced Deep Learning Models for Visual
Recognition”
Yan Zhao: PhD, University of Wollongong (Supervision Panel)
Topic:“Deep Learning: Theories and Applications”
Melih Engin: MPhil,
University of Wollongong (Co-supervisor)
Topic: “Deep Learning Techniques for
Image Retrieval”
[Complete]
Jianjia Zhang: PhD, University of Wollongong
(Supervision Panel)
Topic: “Medical
Image Analysis with Advanced Visual Recognition Models”
(PhD granted, now post-doc fellow at Data61, Sydney)
Huangjing Ni: Visiting PhD, (complete,
Co-supervisor)
Topic: “Exploring Multifractal-based features for the Diagnosis of
Alzheimer’s Disease”
(now post-doc fellow at Brainnetome Center, Institute of Automation, Chinese Academy of
Sciences)
Gentian Li: Visiting Undergraduate (complete, advisor)
Topic:
“Reconstructing Tractography from Brain Diffusion Tensor Imaging (DTI) for
Neuroimage Analysis”
Teaching
Subject Coordinator & Lecturer: CSIT121/821 Object Oriented Design
& Programming (Java), UOW, Autumn Session 2017
Subject Coordinator & Lecturer: CSCI446/946 Multimedia Content
Management, UOW, Spring Session 2016
Subject Coordinator & Lecturer: CSCI433/933 Pattern Recognition,
UOW, Autumn Session 2016
Subject Coordinator & Lecturer: CSCI103 Algorithms and Problem
Solving, UOW, Spring Session 2015
Guest Lecturer: CSCI336 Computer Graphics, UOW, 2014 (OpenGL and GLUT
programming)
Guest Lecturer: CSCI446/946 Multimedia Content Management, UOW, 2014
(Shape Descriptor)
Guest Lecturer: CSCI336 Computer Graphics, UOW, 2013 (OpenGL and GLUT
programming)
Administrative Duties
APD
(Academic Program Director) of Master of Computer Science in CCNU-UOW joint
institute
One of the three APDs of Master
of Computer Science in SCIT, UOW
Research
Activities
Guest
editor for the
special issue on
“High Performance Computing in Bio-medical Informatics” (HPC-BMI) with Neuroinformatics (Springer),
2017.
Organising committee of MICCAI 2019, Hongkong,
2019
Succeeded in DECRA (Discovery Early
Career Researcher Award) 2016-2018 from ARC (Australian Research Council)
Listed in
MICCAI’15 Best Reviewers Runner-ups (14 in total over 700 Peer Reviewers),
Munich, Germany, MICCAI 2015
Guest
editor for special issue “Machine Learning in Medical Imaging”
with Pattern Recognition (Elsevier),
2015-2016
Invited
talk at BrainKDD2015
(Data Mining for Brain Science), hosted by ACM SIGKDD, Sydney, Australia,
Aug. 2015
Co-chair MICCAI15
workshop MLMI2015
(Machine Learning in Medical Imaging), Munich, Germany, Oct. 2015
Co-chair MICCAI14
workshop MLMI 2014 (Machine
Learning in Medical Imaging), Boston,
USA, Sep. 2014
Co-chair ICDM14
workshop DMMI2014
(Data Mining in Medical Imaging), Shenzhen, China, Dec. 2014.
Serve DICTA
2014 as the publicity chair, Wollongong, Australia,
Dec. 2014
Program
Committee: MICCAI-MLMI
(Machine Learning in Medical Imaging) 2011-2016, MICCAI-CMMI
(Computational Methods for Molecular Imaging) 2014-2015, MICCAI-MCV
(Medical Computer Vision) 2015-2016, BrainKDD 2016,
ICIG 2015,
PSIVT 2013, ISNN2010
Grant
Reviewer:
Nov
Project, Breast Cancer Now, UK, 2016
Discovery
Project, Australian Research Council (ARC), Australia, 2016
DECRA,
Australian Research Council (ARC), Australia, 2016
Biomedical
Junior Fellowship, Alzheimer’s Society, UK, 2016
ASDI
research proposal, the Netherlands e-Science Center
(NLeSC) and the Netherlands Organisation for
Scientific Research (NWO), 2015
“Memorable” programme, The Netherlands
Organisation for Health Research and Development (ZonMw)
and the National Initiative Brain & Cognition (NIHC), 2014
Paper
Reviewer: IEEE Trans. on Medical Imaging (TMI), IEEE Trans. on Biomedical
Engineering (TBME), IEEE Journal on Biomedical and Health Informatics (JBHI), IEEE Trans. on
Computational Biology and Bioinformatics (TCBB),
Computerized Medical Imaging and Graphics (CMIG), Machine Vision and
Application (MVA), Information Sciences, IEEE Trans on Circuits and Systems
for Video Technology (TCSVT), Pattern Recognition, Neuroimage, PLoS One, Human Brain Mapping, Brain Connectivity,
Cognitive Computation, Scientific Report, BMC Bioinformatics, MICCAI
2010-2016, AAAI 2015, MLMI 2011-2015, etc.
Visit /
Talk @:
Australian e-Health Research Centre, CSIRO, Brisbane, Australia, 2016
Faculty of
Engineering, Architecture and Information Technology, University of Queensland, Australia,
2016
School of Biomedical Engineering, Zhejiang
University, China, 2016
School of Computer Science and Technology, Nanjing
Normal University, China, 2015
Department of Computer Science, Nanjing University
of Aeronautics and Astronautics, China, 2015
State Key Laboratory for Novel Software Technology, Nanjing
University, China, 2015
Wollongong
Hospital, NSW, Australia, 2015
Biomedical
& Multimedia Information Technology (BMIT) Research Group, University of
Sydney, Australia, 2015
Biodesign Institute and Data Mining Machine Learning Lab,
Arizona State University, USA, 2013
Machine Learning and Cognition Lab, Nanjing Normal
University, China, 2013
Department of Computer Science, Nanjing University
of Aeronautics and Astronautics, China, 2013
School of Computer, National University of Defence
Technology, China, 2013
The Affiliated Sixth People’s Hospital, Shanghai Jiaotong University, China, 2013
Jiangsu Provincial People’s Hospital, Nanjing,
China, 2013
Advanced Analytics Institute, University of
Technology Sydney, Australia, 2013
Illawarra Health and Medical Research Institute,
University of Wollongong, Australia, 2012
Austin Hospital, Melbourne, Australia, 2011, 2012
Australian e-Health Research Centre, Brisbane,
Australia, 2009
Chair for
Computer Aided Medical Procedures & Augmented Reality (CAMP), Technical
University of Munich, Germany, June~August 2009
|
|
