Automatic Head MRI segmentation combining FCM and VBM

DOI

10.2991/amcce-17.2017.98How to use a DOI?

Keywords

Image segmentation; FCM algorithm; VBM algorithm

Abstract

In the diagnosis and operation of the brain, there are five kinds of main tissues, such as gray matter, white matter, cerebrospinal fluid, scalp and skull, those need to be segmented from the MRI to sequel accurate three-dimensional head model. Aiming at this problem, this paper proposes a segmentation method combining FCM & VBM algorithm. After the craniocerebral regions were extracted from the original MRI images by the BET algorithm, the brain regions were subdivided to obtain gray matter, white matter and cerebrospinal fluid by FCM algorithm. Then, the skull, scalp and brain were segmented by VBM segmentation algorithm. And then the smooth and morphological treatment of the separated tissues was carried out. Finally, five kinds of tissues were obtained. Compared with K-means clustering algorithm and morphological segmentation method, it is found that the segmentation algorithm has lower morphological distortion in the case of higher edge gradient.

Copyright

© 2017, 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  - Nan He
AU  - Jun Liu
AU  - HeLei Wu
PY  - 2017/03
DA  - 2017/03
TI  - Automatic Head MRI segmentation combining FCM and VBM
BT  - Proceedings of the 2017 2nd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2017)
PB  - Atlantis Press
SP  - 551
EP  - 558
SN  - 2352-5401
UR  - https://doi.org/10.2991/amcce-17.2017.98
DO  - 10.2991/amcce-17.2017.98
ID  - He2017/03
ER  -