A Support Vector Machine Based Algorithm for Magnetic Resonance Image Segmentation

被引：5

作者：

Du, Xinyu ^{[1
]}

Li, Yongjie ^{[1
]}

Yao, Dezhong ^{[1
]}

机构：

[1] Univ Elect Sci & Technol China, Ctr Neuroinformat, Chengdu, Peoples R China

来源：

ICNC 2008: FOURTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 3, PROCEEDINGS | 2008年

关键词：

D O I：

10.1109/ICNC.2008.400

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this work, we propose a kind of supervised classification-support vector machine (SVM) to segment magnetic resonance image (MRI). As a classifier, SVM can employ structural risk minimization principle and perform better in classification task. Based on those excellent capabilities of SVM, we conduct many detailed experiments on some standard simulated data and real data. According to the experiments results, SVM is proven to be a good classifier in MRI segmentation.

引用

页码：49 / 53

页数：5

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