Breast thermography images are a new type of data that has been analyzed in recent years in order to detect abnormalities, which can lead to a future breast cancer. This paper proposes a methodology for breast thermal image classification, which is useful in Computer-Aided Detection Systems. The main contribution is an automatic method to segment the region of interest (ROI) based on local operations, local analysis, interpolation and statistical operators. For our experiments, we used an image database that is widely used in this research area, obtaining accuracy results between 90.17% and 98.33%, which are competitive with respect to related works.

中文翻译：

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自动感兴趣区域分割以进行乳房热像图图像分类

乳房热成像图像是近年来已被分析以检测异常的新型数据，异常可能导致未来的乳腺癌。本文提出了一种用于乳房热图像分类的方法，该方法可用于计算机辅助检测系统。主要贡献是基于局部操作，局部分析，内插和统计运算符的兴趣区域（ROI）分割的自动方法。对于我们的实验，我们使用了一个在该研究领域中广泛使用的图像数据库，获得了90.17％到98.33％的准确度结果，这在相关作品方面具有竞争力。