计算机科学 ›› 2015, Vol. 42 ›› Issue (5): 315-319.doi: 10.11896/j.issn.1002-137X.2015.05.064
陈 娜,蒋 芸,邹 丽,沈 建,胡学伟,李志磊
CHEN Na, JIANG Yun, ZOU Li, SHEN Jian, HU Xue-wei and LI Zhi-lei
摘要： 随着计算机技术的发展,越来越多的医学图像分析技术应运而生。利用数据挖掘方法对医学图像做分析是目前研究的热点之一,该方法首先从医学图像中提取统计特征,在此基础上进一步挖掘,这种方法对所提取的特征有很强的依赖性而且受到经验等主观因素的影响。针对乳腺X光图像,采用一种可以从图像中自动学习特征并利用学习到的特征对图像进行分类的医学图像分析新方法——判别式受限玻尔兹曼机(Discriminative Restricted Boltzmann Machine,DRBM)。DRBM是一种无向判别模型,它可以自动地从图像中学习特征。在乳腺X光图像标准数据集上的实验结果表明,DRBM对医学图像的分类准确率明显高于其它基于统计特征提取的医学图像分类方法。
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