Statistical morphological skull stripping of adult and infant MRI data

被引：39

作者：

Chiverton, John ^{[1
]}

Wells, Kevin

Lewis, Emma

Chen, Chao

Podda, Barbara

Johnson, Declan

机构：

[1] Univ Surrey, Sch Elect & Phys Sci, Ctr Vis Speech & Signal Proc, Surrey GU2 7XH, England

[2] Univ Cagliari, Dept Elect & Elect Engn, Cagliari, Italy

[3] St George Hosp, Sch Med, London SW17 0RE, England

来源：

COMPUTERS IN BIOLOGY AND MEDICINE | 2007年 / 37卷 / 03期

基金：

英国工程与自然科学研究理事会;

关键词：

mathematical morphology; image processing; skull stripping; MRI; neurological; infant;

D O I：

10.1016/j.compbiomed.2006.04.001

中图分类号：

Q [生物科学];

学科分类号：

07 [理学]; 0710 [生物学]; 09 [农学];

摘要：

This paper describes a novel automatic statistical morphology skull stripper (SMSS) that uniquely exploits a statistical self-similarity measure and a 2-D brain mask to delineate the brain. The result of applying SMSS to 20 MRI data set volumes, including scans of both adult and infant subjects is also described. Quantitative performance assessment was undertaken with the use of brain masks provided by a brain segmentation expert. The performance is compared with an alternative technique known as brain extraction tool. The results suggest that SMSS is capable of skull-stripping neurological data with small amounts of over- and under-segmentation. (c) 2006 Elsevier Ltd. All rights reserved.

引用

页码：342 / 357

页数：16

共 35 条

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