Knowledge-driven segmentation of the central sulcus from human brain MR images

被引：0

作者：

Zuo, W ^{[1
]}

Hu, QM ^{[1
]}

Aziz, A ^{[1
]}

Loe, K ^{[1
]}

Nowinski, WL ^{[1
]}

机构：

[1] Bioinformat Inst, Biomed Imaging Grp, Singapore, Singapore

来源：

ICIP: 2004 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1- 5 | 2004年

关键词：

central sulcas; segmentation; MRI; human brain; neuroinformatics;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

This paper presents a knowledge-driven algorithm to identify and segment the central suclus (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 suclus 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.

引用

页码：2443 / 2446

页数：4

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