钙化信息是乳腺癌早期诊断的一个重要依据，针对乳腺图像钙化信息受背景组织以及噪声影响而可视性差的问题，提出一种基于形状选择性滤波和自适应背景抑制的乳腺钙化图像增强算法。首先利用形状选择性滤波器提取出潜在非线状钙化信息，将钙化图像分为前景和背景区域；然后对背景信息的对比度进行自适应抑制，同时对前景钙化信息进行对比度增强处理，最后达到有选择地实现乳腺钙化图像中关键信息的可视化增强。实验结果表明，该方法可有针对的选择钙化区域进行对比度增强，同时可有效抑制背景图像中血管、组织等正常区域对钙化区域的影响。

The microcalcification information is an important foundation for the diagnosis of breast cancers. In order to improve the badly vision of microcalcifications which are affected by noises and tissues, a novel enhancement algorithm of mammograms based on shape-selective filter and adaptive background suppression is presented. First the potential non-linear microcalcifications are detected by using shape-selective filter, and then the mammograms are divided into foreground and background sections. Second the background information is suppressed by using an adaptive contrast suppression method, and the foreground information is enhanced at the same time, then the key information of the mammograms is enhanced selectively. Experimental results show that this algorithm can enhance the microcalcification images and suppress the influence of blood vessels and tissues.