MR brain image segmentation using an enhanced fuzzy C-means algorithm

被引：360

作者：

Szilágyi, L ^{[1
]}

Benyó, Z ^{[1
]}

Szilágyi, SM ^{[1
]}

Adam, HS ^{[1
]}

机构：

[1] Budapest Univ Technol & Econ, Dept Control Engn & Informat Technol, Budapest, Hungary

来源：

PROCEEDINGS OF THE 25TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4: A NEW BEGINNING FOR HUMAN HEALTH | 2003年 / 25卷

关键词：

MR imaging; image segmentation; fuzzy logic;

D O I：

10.1109/IEMBS.2003.1279866

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

This paper presents a new algorithm for fuzzy segmentation of MR brain images. Starting from the standard FCM [1] and its bias-corrected version BCFCM [2] algorithm, by splitting up the two major steps of the latter, and by introducing a new factor gamma, the amount of required calculations is considerably reduced. The algorithm provides good-quality segmented brain images a very quick way, which makes it an excellent tool to support virtual brain endoscopy. This research has been supported by the Hungarian National Research Fund, Grants No. OTKA T042990 and T029830.

引用

页码：724 / 726

页数：3

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