Seed Extension Based Interactive Medical Volume Segmentation Method

DOI

10.2991/icaita-16.2016.57How to use a DOI?

Keywords

component; interactive segmentation; medical image processing; graph cuts; minimum spanning forests

Abstract

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.

Copyright

© 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/).

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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  -