| 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. |
