2007 IEEE International Conference on Image Processing - San Antonio, Texas, U.S.A. - September 16-19, 2007

Technical Program

Paper Detail

Paper:MP-P6.4
Session:Biomedical Imaging I
Time:Monday, September 17, 14:30 - 17:10
Presentation: Poster
Title: A 3D SELF-ADJUST REGION GROWING METHOD FOR AXON EXTRACTION
Authors: Kai Zhang; Shanghai Jiao Tong University 
 Hongkai Xiong; Shanghai Jiao Tong University 
 Xiaobo Zhou; Harvard Medical School, Brigham and Women's Hospital 
 Stephen Wong; Harvard Medical School, Brigham and Women's Hospital 
Abstract: Neuron axon analysis is an important means to investigate disease mechanisms and signaling pathways in neurobiology and often requires collecting a great amount of statistical information and phenomena. Automated extraction of axons in 3D microscopic images posts a key problem in the field of neuron axon analysis. To address tortuous axons in 3D volumes, a self-adjust region growing approach referring to surface modeling and self-adjustment which takes advantage of the nature of axon (e.g., continuity), is presented. Experimental results on axon volumes show that the proposed scheme provides a reliable solution to axon retrieving and overcomes several common drawbacks from other existing methods.



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