A 2-D automatic segmentation scheme for brainstem and cerebellum regions in brain MR imaging

Jiann Der Lee*, Yeo Xiang Tseng, Li Chang Liu, Chung Hsien Huang, Shin Tseng Lee, Chien Tsai Wu, Jyi Feng Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

This paper describes a 2-D automatic segmentation scheme for brainstem and cerebellum regions in brain MR images by using Ada-boosted and Active Contour Model technologies. The proposed scheme includes two processing stages: the detection process for the candidate regions and the segmentation process for the final contours. In the detection process, Ada-boosted technology has been used for three times to find the large region containing the brainstem and cerebellum first and to find the individual cerebellum and brainstem candidate regions later. The partial edge information of candidate regions are used as boundary limits in the next stage. In the segmentation process, a modified Scale-based Fuzzy Connectedness algorithm (SFC), Chain code, and Active Contour Model (ACM) are used for the final boundaries. This automatic scheme provides consistent segmentation results to avoid manual errors such as the seed locations in Fuzzy Connectedness methods.

Original languageEnglish
Title of host publicationProceedings - Fourth International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2007
Pages270-274
Number of pages5
DOIs
StatePublished - 2007
Event4th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2007 - Haikou, China
Duration: 24 08 200727 08 2007

Publication series

NameProceedings - Fourth International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2007
Volume4

Conference

Conference4th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2007
Country/TerritoryChina
CityHaikou
Period24/08/0727/08/07

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