NDLI: A fast atlas pre-selection procedure for multi-atlas based brain segmentation

Content Provider	IEEE Xplore Digital Library
Author	Jingbo Ma Ma, H.T. Hengtong Li Chenfei Ye Dan Wu Xiaoying Tang Miller, M. Mori, S.
Copyright Year	2015
Description	Author affiliation: Shenzhen Grad. Sch., Dept. of Electron. & Inf. Eng., Harbin Inst. of Technol., Shenzhen, China (Jingbo Ma; Ma, H.T.; Hengtong Li; Chenfei Ye) \|\| Radiol. Dept., Johns Hopkins Univ., Baltimore, MD, USA (Dan Wu; Mori, S.) \|\| Center for Imaging Sci., Johns Hopkins Univ., Baltimore, MD, USA (Xiaoying Tang; Miller, M.)
Abstract	Multi-atlas based MR image segmentation has been recognized as a quantitative analysis approach for brain. For such purpose, atlas databases keep increasing to include various anatomical characteristics of human brain. Atlas pre-selection becomes a necessary step for efficient and accurate automated segmentation of human brain images. In this study, we proposed a method of atlas pre-selection for target image segmentation on the MriCloud platform, which is a state-of-the-art multi-atlas based segmentation tool. In the MRIcloud pipeline, segmentation of lateral ventricle (LV) label is generated as an additional input in the segmentation pipeline. Under this circumstance, similarity of the LV label between target image and atlases was adopted as the atlas ranking scheme. Dice overlap coefficient was calculated and taken as the quantitative measure for atlas ranking. Segmentation results based on the proposed method were compared with that based on atlas pre-selection by mutual information (MI) between images. The final segmentation results showed a comparable accuracy of the proposed method with that from MI based atlas pre-selection. However, the computation load for the atlas pre-selection was speeded up by about 20 times compared to MI based pre-selection. The proposed method provides a promising assistance for quantitative analysis of brain images.
Starting Page	3053
Ending Page	3056
File Size	804665
Page Count	4
File Format	PDF
ISSN	1557170X
e-ISBN	9781424492718
DOI	10.1109/EMBC.2015.7319036
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-25
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Pipelines Databases Accuracy Brain Mutual information Magnetic resonance imaging
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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