Li Wang's homepage

Welcome to Li Wang's homepage.

I am a postdoctoral research associate from the University of North Carolina at Chapel Hill, USA.
I work with Prof. Dinggang Shen in Medical Image Analysis field.
My research interests focus on segmentation, registration, cortical surface analysis,
and their applications on normal early brain development and disorders.

This page is under construction and will be ready soon.
Contact: li_wang@med.unc.edu

Publication

1. Li Wang, Feng Shi, Pew-Thian Yap, Weili Lin, John H. Gilmore, Dinggang Shen. Longitudinally guided level sets for consistent tissue segmentation of neonates. Human Brain Mapping. 2011.[PDF] [Infant processing package]

2. Jingxin Nie, Gang Li, Li Wang, John H. Gilmore, Weili Lin, Dinggang Shen. "Computational Growth Model for Measuring Dynamic Cortical Development in the First Year of Life", accepted for Cerebral Cortex.

3. Jingxin Nie, Gang Li, Li Wang, John H. Gilmore, Weili Lin, and Dinggang Shen. "Computational Growth Model for Cortical Development in the First Year of Life", Image Analysis of Human Brain Development (IAHBD 2011), Toronto, Canada, Sep. 22, 2011.

4. Minjeong Kim, Guorong Wu, Wei Li, Li Wang, Young-Don Son, Zang-Hee Cho, and Dinggang Shen. "Segmenting Hippocampus from 7.0 Tesla MR Images by Combining Multiple Atlases and Auto-Context Models", MLMI 2011, Toronto, Canada, Sep. 18, 2011.

5. Li Wang, Feng Shi, Weili Lin, John H. Gilmore, Dinggang Shen. "Automatic Segmentation of NeonatalImages Using Convex Optimizationand Coupled Level Sets", NeuroImage, 58:805-817, 2011. [PDF] [Infant processing package]

6. Feng Shi, Li Wang, John H. Gilmore, Weili Lin, Dinggang Shen. Learning-based Meta-Algorithm for MRI Brain Extraction”, MICCAI 2011, Toronto, Canada, Sep. 18-22, 2011.

7. Li Wang, Feng Shi, John H. Gilmore, Weili Lin, Dinggang Shen. Longitudinal guided level-sets for consistent neonatal image segmentation. ISMRM'11, Montreal, Quebec, Canada, May 7-13, 2011

8. Li Wang, Feng Shi, John H. Gilmore, Weili Lin, Dinggang Shen. Automatic Segmentation of Neonatal Images Using Convex Optimization and Coupled Level Set Method. MIAR 2010, LNCS, Volume 6326/2010, 1-10, Beijing, China, Sep. 19-20, 2010.(Oral presentation)[PDF] [Code(Linux)]

9. Li Wang, Lei He, Arabinda Mishra, Chunming Li. Active Contours Driven by Local Gaussian Distribution Fitting Energy. Signal Processing, 89(12), 2009,p. 2435-2447 [PDF] [Email request for the code]

10. Chunming Li, Chris Gatenby, Li Wang, and John Gore. A Robust Parametric Method for Bias Field Estimation and Segmentation of MR Images. IEEE conference on Computer Vision and Pattern Recognition (CVPR) , 2009

11. Li Wang, Chunming Li, Quansen Sun, Deshen Xia, Chiu-Yen Kao. Active contours driven by local and global intensity fitting energy with application to brain MR images segmentation. Computerized Medical Imaging and Graphics, 33(7), 2009, p.520-531 [PDF]

12. Li Wang, Chunming Li, Quansen Sun, Deshen Xia, Chiu-Yen Kao. Brain MR image segmentation using local and global intensity fitting active contours/surfaces. In: Proceedings of medical image computing and computer aided intervention (MICCAI), vol. LNCS 524, 619 Part I. 2008. p.384-392

Research & Source Code

1. Medical Image Segmentation with Local Gaussian Distribution (LGD) Fitting Energy [PDF] [Email request for the code]

2. Infant Brain Segmentation: Longitudinally guided level sets for consistent tissue segmentation of neonates. Human Brain Mapping. 2011.[PDF] [Source code: Infant processing package]

3. Extraction of the Cerebral Cortical Boundaries (TBA) (click the image to see the high resolution)

4. Segmentation of Adult Brain MR Images (TBA)

Education

Nanjing University of Science and Technology
Ph.D., Pattern Recognition and Intelligent System, 2005-2010

Nanjing Agricultural University
M.S., Town and Country Planning, 2001-2005

Li Wang