Automatic Segmentation of Spleen based on Anatomical Model and Template Matching

DOI

10.2991/cisia-15.2015.159How to use a DOI?

Keywords

template matching; organ bounding box; spleen segmentation; probabilistic atlas

Abstract

Probabilistic atlases based on human anatomy structure have been widely used for organ segmentation, which is used as a prior probability in a Bayes framework. The challenge is how to register the probabilistic atlas to the patient volume. Taking these into consideration, we propose a template matching framework based on the probabilistic atlas for spleen segmentation. Firstly, we find a bounding box of the spleen based on human anatomical localization, which is the statistical geometric location of spleens. Then, the probabilistic atlas is used as a template to find the spleen in this bounding box by using template matching technology. We apply our method into 60 datasets including normal and pathological cases. The Dice/Tanimoto volume overlaps are 0.922/0.857, the root-mean-squared error (RMSE) is 1.992 mm. The algorithm is robust to segment normal and abnormal spleens, such as the presence of tumors and large morphological changes. Meanwhile, our proposed method was compared with conventional atlas-based methods. Results demonstrate that segmentation accuracy improved using our method.

Copyright

© 2015, 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  - C.H Dong
AU  - X.H Han
AU  - T. Tateyama
AU  - Y.W Chen
AU  - A.H Foruzan
PY  - 2015/06
DA  - 2015/06
TI  - Automatic Segmentation of Spleen based on Anatomical Model and Template Matching
BT  - Proceedings of the International Conference on Computer Information Systems and Industrial Applications
PB  - Atlantis Press
SP  - 585
EP  - 588
SN  - 2352-538X
UR  - https://doi.org/10.2991/cisia-15.2015.159
DO  - 10.2991/cisia-15.2015.159
ID  - Dong2015/06
ER  -