Universidade Federal de Minas Gerais, Departamento de Ciência da Computação, Av. Antônio Carlos, 6627, 31270-901, Belo Horizonte, MG, Brazil.
Comput Methods Programs Biomed. 2010 Sep;99(3):289-97. doi: 10.1016/j.cmpb.2010.01.005. Epub 2010 Mar 7.
In this paper, we present a content-based image retrieval system designed to retrieve mammographies from large medical image database. The system is developed based on breast density, according to the four categories defined by the American College of Radiology, and is integrated to the database of the Image Retrieval in Medical Applications (IRMA) project, that provides images with classification ground truth. Two-dimensional principal component analysis is used in breast density texture characterization, in order to effectively represent texture and allow for dimensionality reduction. A support vector machine is used to perform the retrieval process. Average precision rates are in the range from 83% to 97% considering a data set of 5024 images. The results indicate the potential of the system as the first stage of a computer-aided diagnosis framework.
本文提出了一个基于内容的医学图像检索系统,旨在从大型医学图像数据库中检索乳腺 X 光片。该系统是根据美国放射学院定义的四类乳腺密度开发的,并集成到医学图像检索应用(IRMA)项目的数据库中,该数据库提供了具有分类真实标签的图像。二维主成分分析用于乳腺密度纹理特征化,以有效地表示纹理并允许降维。支持向量机用于执行检索过程。考虑到 5024 张图像的数据集,平均精度率在 83%到 97%之间。结果表明,该系统作为计算机辅助诊断框架的第一阶段具有潜力。