Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICIP.2004.1421595
Title: Knowledge-driven segmentation of the central sulcus from human brain MR images
Authors: Zuo, W.
Hu, Q.
Aziz, A.
Loe, K. 
Nowinski, W.L.
Keywords: Central sulcus
Human brain
MRI
Neuroinformatics
Segmentation
Issue Date: 2004
Source: Zuo, W.,Hu, Q.,Aziz, A.,Loe, K.,Nowinski, W.L. (2004). Knowledge-driven segmentation of the central sulcus from human brain MR images. Proceedings - International Conference on Image Processing, ICIP 4 : 2443-2446. ScholarBank@NUS Repository. https://doi.org/10.1109/ICIP.2004.1421595
Abstract: This paper presents a knowledge-driven algorithm to identify and segment the central sulcus (CS) from human brain MR images. The dataset is reformatted along the anterior and posterior commissures (AC-PC) plane first. Then, the 3D region within the two coronal planes passing through the AC and PC is defined as the region of interest (ROI) to search for all the sulci within it. The CS is the sulcus with the largest volume within the ROI. Together with the sulci, grey matter (GM) is included for the region growing in order to deal with the partial volume effect. The GM is removed through skeletonization. Experimental results are given. © 2004 IEEE.
Source Title: Proceedings - International Conference on Image Processing, ICIP
URI: http://scholarbank.nus.edu.sg/handle/10635/41841
ISBN: 0780385543
ISSN: 15224880
DOI: 10.1109/ICIP.2004.1421595
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

58
checked on Dec 9, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.