Seed Extension Based Interactive Medical Volume Segmentation Method
- 10.2991/icaita-16.2016.57How to use a DOI?
- component; interactive segmentation; medical image processing; graph cuts; minimum spanning forests
This paper proposes an interactive segmentation method based on seed extension to tackle the problems of the min-cut/max-flows algorithm, which was extensively validated for many interactive segmentation applications. The extension is performed by constructing minimum spanning forests (MSF) from seed voxels imposed by users, which minimizes the weights of edges from the seeds to segmented lines (cuts). Compared with the graph cuts-based method, the proposed method segments the volume image into more than two regions of interests. Moreover, the proposed method performs 10 times faster when segmenting volumes composed of more than 240 slices, as the time complexity of constructing MSF is quasi-linear, whereas the min-cut/max-flow is polynomial.
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Anjin Park AU - Hong-Lyel Jung AU - Joo Beom Eom AU - Jaesung Ahn AU - Byeong-Il Lee PY - 2016/01 DA - 2016/01 TI - Seed Extension Based Interactive Medical Volume Segmentation Method BT - Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications PB - Atlantis Press SP - 231 EP - 234 SN - 1951-6851 UR - https://doi.org/10.2991/icaita-16.2016.57 DO - 10.2991/icaita-16.2016.57 ID - Park2016/01 ER -