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  Computer Vision and Pattern Discovery
 
Dr. LEE Hwee Kuan
Principal Investigator

Details
 
 
Research Group Members
 
NameTitle
Dr. LEE Hwee KuanPrincipal Investigator
Dr. HUANG Chao HuiPostdoctoral Fellow (JCO)
Dr. KOH Yang Wei, PatrickPostdoctoral Fellow
Dr. LAW Yan Nei, IvyPostdoctoral Fellow
Mr. YAP Choon KongResearch Associate (TCRP)
Ms. GONG TianxiaResearch Associate (TCRP)
Mr. MOHAMED HanifaSoftware Engineer (TCRP)
 
Research Projects

The group of Computer Vision and Pattern Discovery for Bioimages focuses on applying advanced computer vision, machine learning and mathematical models for the improvement of health care and discovery of biological knowledge. The group analyses images of tissue, histological slides and cell assays. These images were acquired using wide-field, confocal, FCS, and light-sheet microscopes as well as infra-red camera and other kinds of clinical image devices.

In a clinical setting, imaging techniques are becoming important as they are usually non-invasive and advancement of clinical devices has made quantitative analysis of these images an important component for improving health care through the use of technology.

Motivate by the desire to device better cures for diseases and driven by enabling technologies on high-throughput screens, biological experiments are becoming more quantitative and generating large amounts of data. Especially in the area of digital imaging where thousands of images are acquired automatically through robotic systems of chemical and cell assays handling. These images are then analyzed and used to create new biological hypotheses that are further validated using other experimental means. The group's contributions to high throughput, high content imaging are to provide accurate and fast computational methods for the data mining of large image data sets.
 
Computation Meibography   Prostate Project
     
Cellular Phenotype Recognition   Texture Segmentation Using the Subspace Mumford-Shah Model
     
Entropy Regularization Feature Relevance for Texture and its Applications in Bioimage Processing   Field Theoretical Method for Image Restoration
     
Effective segmentation using the evolving generalized voronoi diagram.   Biomedical Image Segmentation of Semi-transparent Objects Using a Variant of the Mumford-Shah Model
     
Quantitative Microscopy for Neural Stem Cells Progenitor Growth and Differentiation   A Multi-resolution Stochastic Level Set Method for the Segmentation of Bioimages
     
Automated Nucleus and Cells Detection using a Region Based Ellipse Detector   Automated Protein Distribution Detection in Images from High-throughput Image-based siRNA Library Screens
 
Imaging Informatics of Stem Cells      
 
 
 
Journal Publications
 
  1. Chao-Hui HUANG, Antoine VEILLARD, Daniel RACOCEANU, Nicolas LOMENIE and Ludovic ROUX
    Time-efficient sparse analysis of histopathological Whole Slide Images
    Computerized Medical Imaging and Graphics,2011;35(7-8):579-91
    Epub 2010 Dec 10


  2. Yan Nei Law, Hwee Kuan Lee, and Andy M. Yip
    Subspace learning for Mumford–Shah-model-based texture segmentation
    through texture patches
    Applied Optics,2011;50(21):3947–3957


  3. Hiroshi Watanabe, Satoshi Sashida, Yutaka Okabe and Hwee Kuan Lee
    Monte Carlo methods for optimizing the piece-wise constant
    Mumford-Shah Segmentation Model
    New J.Phys,2011;13:023004


  4. Mohammad Shorif Uddin, H. K. Lee, Preibisch S, Tomancak P.
    Restoration of uneven illumination in light sheet microscopy images
    Microsc Microanal,2011;17(4):607-13
    Epub 2011 Jun 20


  5. Yan Nei Law, Hwee Kuan Lee, Chaoqiang Liu, Andy M. Yip
    A Variational Model for Segmentation of Overlapping Objects with Additive Intensity Value
    IEEE Trans. Img. Proc,2011; 20(6): 1495-1503.
    link: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5659480


  6. Zong Hong Zhang, Hwee Kuan Lee and Ivana Mihalek.
    Reduced representation of protein structure: implications on efficiency and scope of detection of structural similarity.
    BMC Bioinformatics,2010;11:155


  7. Jagadish Sankaran, Xianke Shi, Liang Yoong Ho, Ernst H.K. Stelzer, and Thorsten Wohland
    ImFCS: A software for Imaging FCS data analysis and visualization
    Optics express,2010;18(25):25468-25481


  8. Yan Nei Law, Andy M. Yip and Hwee Kuan Lee
    Automatic Measurement of Volume Percentage Stroma in Endometrial Images using Texture Segmentation
    Journal of Microscopy, 2011;241(2):171-178


  9. Y.N.Law, H. K. Lee, A. M. Yip
    Semi-supervised Subspace Learning for Mumford-Shah Model Based Texture Segmentation
    Optics Express,2010;18(5):4934-4448


  10. W. Yu, H. K. Lee et al
    Evolving Generalized Voronoi Diagram of Active Contours for Accurate Cellular Image Segmentation
    Cytometry Part A,2010;77A:379-386


  11. Hwee Kuan Lee, Mohammad Shorif Uddin, Shvetha Sankaran, Srivats Hariharan, Sohail Ahmed
    A field theoretical restoration method for images degraded by non-uniform light attenuation : an application for light microscopy
    Optics Express,2009;17(14):11294-11308
    (selected to be published again in the Virtual Journal of Biomedical Optics, 2009; 4: 11294-11308)


  12. W. Yu, H. K. Lee, S. Hariharan, W. Y. Bu, S. Ahmed
    Quantitative Neurite Outgrowth Measurement Based on Image Segmentation with Topological Dependence
    Cytometry A,2008;75A:289-297


  13. Yan Nei Law, Hwee Kuan Lee and Andy M. Yip
    A Multi-resolution Stochastic Level Set Method for Mumford-Shah Image Segmentation
    IEEE Trans. Img. Proc.,2008;17(12):2289-2300
    CAM Report 07-43 (2007) http://www.math.ucla.edu/applied/cam/


  14. Y. N. Law, S. Ogg, et al.
    Automated Protein Distribution Detection in High-Throughput Image-Based siRNA Library Screens
    Journal of Signal Processing Systems,2009;55:1-13
 
Conference Proceedings
 
  1. Chao-Hui HUANG
    Bio-inspired Computer Visual System and its Applications
    Decade Of The Mind VI, Singapore, 2011

  2. Chao-Hui HUANG, Daniel RACOCEANU, Ludovic ROUX, Thomas C.PUTTI
    Bio-inspired Computer Visual System using GPU and Visual Pattern Assessment Language (ViPAL): Application on Breast Cancer Prognosis
    International Conference on Neural Networks(IJCNN2010) Barcelona, Spain, 18-23 July 2010

  3. Yan Nei Law, Hwee Kuan Lee and Andy M. Yip
    A Stochastic Level Set Method for Subspace Mumford-Shah Based Image
    Segmentation
    Proc. of the 2011 Intl. Conf. on Image Processing,Computer Vision and
    Pattern Recognition

  4. Yan Nei Law, Hwee Kuan Lee, Michael K. Ng, and Andy M. Yip
    Interactive Segmentation of Multiple Images
    Proc. of the 2011 Intl. Conf. on Image Processing, Computer Vision and
    Pattern Recognition

  5. Yan Nei Law, Hwee Kuan Lee and Andy M. Yip
    Subspace Descriptor for Texture and its Applications
    Proc. of the 2010 Intl. Conf. on Image Processing,Computer Vision and Pattern Recognition.


  6. Yan Nei Law, Hwee Kuan Lee and Andy M. Yip
    A Subspace Clustering Model for Image Texture Segmentation
    Proc. of 5th European Conference on Computational Fluid Dynamics


  7. W. Yu, H. K. Lee et al
    Segmentation of Neural Stem/Progenitor Cells Nuclei within 3-D Neurospheres
    Int. Sym. Visual Computing, (ISVC 2009). Lecture Notes in Computer Science, 2009; 5875: 531-543


  8. Q. Ho, W. Yu , H. K. Lee
    Region Graph Spectra as Geometric Global Image Features
    Int. Sym. Visual Computing, (ISVC 2009). Lecture Notes in Computer Science,2009;5875: 253-264


  9. W. Yu, H.K. Lee et al
    Detection and Quantitative Measurement of Neuronal Outgrowth in Fluorescence Microscopy Images
    Proc. of the Medical Image Understanding and Analysis (MIUA) 2009.


  10. YN Law, HK Lee, AM Yip
    Supervised Texture Segmentation Using the Subspace Mumford-Shah Model
    Proc. of the 2009 Intl. Conf. on Image Processing, Computer Vision and Pattern Recognition (IPCV09).


  11. YN Law, HK Lee, C Liu, AM Yip
    Segmentation of Semi-transparent Objects Using a Variant of the Mumford-Shah Model
    Proc. of the 2009 Intl. Conf. on Image Processing, Computer Vision and Pattern Recognition (IPCV09).


  12. Choon Kong Yap, Hwee Kuan Lee
    Identification of Cell Nucleus Using a Mumford-Shah Ellipse Detector
    Int. Sym. Visual Computing (ISVC 2008). Lecture Notes in Computer Science,2008;5358:582-593


  13. Weimiao Yu, Hwee Kuan Lee, Srivats Hariharan, Wenyu Bu and Sohail Ahmed
    Level Set Segmentation of Cellular Images Based on Topological Dependence
    Int. Sym. Visual Computing (ISVC 2008). Lecture Notes in Computer Science,2008;5358:540-551(Best Paper Award in ISVC2008)
 

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