NDLI: Automatic parcellation of cortical surfaces using random forests

Content Provider	IEEE Xplore Digital Library
Author	Yu Meng Gang Li Yaozong Gao Dinggang Shen
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Sci., Univ. of North Carolina at Chapel Hill, Chapel Hill, NC, USA (Yu Meng; Yaozong Gao) \|\| Dept. of Radiol. & BRIC, Univ. of North Carolina at Chapel Hill, Chapel Hill, NC, USA (Gang Li; Dinggang Shen)
Abstract	Automatic and accurate parcellation of cortical surfaces into anatomically and functionally meaningful regions is of fundamental importance in brain mapping. In this paper, we propose a new method leveraging random forests and graph cuts methods to parcellate cortical surfaces into a set of gyral-based regions, using multiple surface atlases with manual labels by experts. Specifically, our method first takes advantage of random forests and auto-context methods to learn the optimal utilization of cortical features for rough parcellation and then the graph cuts method to further refine the parcellation for improved accuracy and spatial consistency. Particularly, to capitalize on random forests, we propose a novel definition of Haar-like features on cortical surfaces based on spherical mapping. The proposed method has been validated on cortical surfaces from 39 adult brain MR images, each with 35 regions manually labeled by a neuroanatomist, achieving the average Dice ratio of 0.902, higher than the-state-of-art methods.
Starting Page	810
Ending Page	813
File Size	582178
Page Count	4
File Format	PDF
ISBN	9781479923748
DOI	10.1109/ISBI.2015.7163995
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-04-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accuracy Training Labeling Rough surfaces Surface roughness Feature extraction Testing Haar-like features Cortical surface parcellation random forests context feature graph cuts
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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