I received my Ph.D. degree in
Electrical Engineering from
University of Connecticut in 2005. My Ph.D. advisor
was Prof. Martin D. Fox. Before I came to the U.S., I was trained in mathematics
in China and got my B.S. and M.S. degrees in Math. My research interests
include image processing, computer vision, medical imaging, and applied
mathematics.
Chunming Li, Fang Li, Chiu-Yen Kao, and
Chenyang Xu, "Image Segmentation with Simultaneous Illumination and
Reflectance Estimation: An Energy Minimization Approach", ICCV 2009.
Chunming Li, Chris Gatenby, Li Wang, and John C. Gore, "A Robust Parametric Method for Bias Field
Estimation and Segmentation of MR Images", CVPR 2009.
Chunming Li, Rui Huang, Zhaohua Ding, Chris Gatenby, Dimitris Metaxas,
John Gore, "A Variational Level Set Approach to Segmentation and Bias
Correction of Images with Intensity Inhomogeneity",MICCAI 2008. (Oral presentation),
(pdf,
BibTex,
PPT slides, Code)
Chunming Li, Chiu-Yen Kao, John C. Gore, and Zhaohua Ding, "Minimization
of Region-Scalable Fitting Energy for Image Segmentation",IEEE Trans. Image Processing,
vol 17 (10), 2008. (pdf,
BibTex,
Matlab code:.rar,
.zip
new ).
Chunming Li, Chenyang Xu, Changfeng Gui, and Martin D. Fox, "Regularized
Level Set Evolution and its Application to Image Segmentation",IEEE Trans. Image Processing,
accepted, 2008.
Chunming Li, Chiu-Yen Kao, John C. Gore, and Zhaohua Ding, "Implicit
Active Contours Driven by Local Binary Fitting Energy",CVPR 2007.
(pdf,BibTex,
Demos,
Code)
Chunming Li, Chenyang Xu, Changfeng Gui, andMartin D. Fox, "Level Set Evolution Without Re-initialization: A
New Variational Formulation",CVPR 2005. (Oral presentation). (pdf,
BibTex,
Citations,
Demos,
Matlab code)
Chunming Li, Jundong Liu, and Martin D. Fox, "Segmentation of Edge
Preserving Gradient Vector Flow: An Approach Toward Automatically
Initializing and Splitting of Snakes",CVPR 2005. (pdf,
BibTex,
Demos)
"Variational and Level Set Methods in Image Segmentation", Mathematics
Department, Ohio State University, June 7, 2007. (PPT
slides)
"Vessel Segmentation Using Local Binary Fitting
Active Contours", Mathematics Department,
University of Connecticut,
October, 2006
"Active Contours, Level Sets, and Image Segmentation",
Statistics Department, Florida State University, January, 2006.
"Diffusion Tensor Imaging: Concepts and Processing Techniques"
and "Level Set Methods and Medical Image Segmentation",
Engineering Physics Department, Tsinghua University, December,
2006
"Level Set Evolution without Reinitialization", Mathematics
Department, Vanderbilt University, November, 2005.
"Mathematical Methods in Medical
Imaging", Mathematics Department, Fudan University, October, 2005.
Level Set/Active Contour Models for Image
Segmentation
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Fast narrow band
implementation of the above method, (pdf,
demo code).
Segmentation
of external force field for a snake model, CVPR'05.
Region based models:
A Robust Parametric Method for Bias Field
Estimation and Segmentation of MR Images, CVPR'09. (pdf, BibTex)
Implicit Active
Contours Driven by Local Binary Fitting Energy, CVPR'07. (pdf,BibTex)
Minimization of Region-Scalable Fitting Energy for
Image Segmentation,IEEE Trans. Image Processing, 2008. (pdf,
BibTex).
Implementations of the
original LBF model and
further developments:
LBF_v0. (Matlab
source code for the original LBF model in the above CVPR and
IEEE TIP papers).
LBF_v0.1
(.rar
or .zip)
for Matlab 7.0 or
higher versions in Windows. (Note: this version is an improvement of
LBF_v0, much more robust to contour initialization).
Segmentation of
brain MR images with intensity inhomogeneity. This model is able to
simultaneously segment gray matter, white matter, cerebrospinal fluid (CSF),
and the background.
One page abstract to appear inISMRM'08 (oral presentation).
3D versions:
Implementations of
other level set/active contour methods: