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Decomposition of branching volume data by tip detection

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4 Author(s)
Wei Ma ; Key Lab. of Machine Perception (Minist. of Educ.), Peking Univ., Peking ; Bo Xiang ; Xiaopeng Zhang ; Hongbin Zha

We present an approach to decomposing branching volume data into sub-branches. First, a metric is proposed for evaluating local convexities in volumetric data, and it is a criterion for global selection of tip points. Second, a multi-path growing strategy is adopted to segment the volumes based on a DFS transformation starting from the tips. Experiments show that this approach is capable of generating desirable components and reasonable segmentation boundaries of a volume.

Published in:

Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on

Date of Conference:

12-15 Oct. 2008