基于支持向量机的乳腺MRI分类

Chuin-Mu Wang, Xiao-Xing Mai, G. Lin, Chio-Tan Kuo
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引用次数: 33

摘要

磁共振成像对人体无害,近年来在临床试验中得到广泛应用。在本研究中,我们想要从多光谱MR图像中检测乳腺组织。由于多光谱磁共振图像是对同一切片进行不同频率和参数的扫描,可以获得完整的信息。在图像分类中,我们将支持向量机(SVM)应用于乳房多谱磁共振图像,分别对乳房组织进行分类。分类结果有助于医生对乳腺肿瘤进行判断和筛选。为了进一步评价其性能,将c均值(CM)分类方法与支持向量机进行比较。通过一些实验,SVM的结果优于c均值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Classification for Breast MRI Using Support Vector Machine
Magnetic resonance image (MRI) was harmless to the human body and used on the clinical trial extensively in recent years. In this study, we want to detect the tissues of breast form the multi-spectral MR image. Because multi-spectral MR image are scanning the same slice with various frequencies and parameters and it can obtain intact information. In the image classification, we apply support vector machine (SVM) on breast multi-spectral magnetic resonance image to classify the tissues of breast separately. The classification results would assist doctor to judge and sift the breast tumor. In order to further evaluate its performance, the C-means (CM) classification method is compared with SVM. By some experiments, the result of SVM is better than C-mean.
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