Abstract
We propose a general-purposed parallel algorithm for volume segmentation, which does not require any prior knowledge on volume nor region. The algorithm provides binary tree structured split-and-merge mechanism to search and localize boundaries along discontinuities and adapts the partition of volume to those detected discontinuities. This algorithm is independent from order of processing or seed selection and maintains consistencies of adjacent process blocks without their interprocess communication. Our efficient hierarchical step-wised mechanism in merging target evaluation makes merge process so simple and efficient that only two blocks with the same parents are considered at each merge step in binary fashion. Experimental results on an artificial and a CT scan volume data are shown.
