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Automatic Segmentation and Detection of Mass in Digital Mammograms

机译:数字乳房X线照片中的质量自动分割和检测

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摘要

This paper presents an automated system for mass segmentation and detection in mammograms. Initially, breast segmentation is applied to separate the breast and non-breast area. Then, image enhancement is employed to improve the contrast of the tissues structure in mammograms. Finally, constraint region growing based on local statistical texture analysis is applied to detect and segment out the mass from the mammograms. The system is develop and evaluated with 322 mammograms from Mammographic Image Analysis Society Database. The verification results show that the proposed technique has a sensitivity of 94.59% and the number of false positive per image is 3.90.
机译:本文提出了一种自动系统,用于乳房X线照片的质量分割和检测。最初,将乳房分割用于分离乳房和非乳房区域。然后,采用图像增强来改善乳房X光照片中组织结构的对比度。最后,基于局部统计纹理分析的约束区域增长被应用于从乳房X线照片中检测并分割出肿块。该系统是根据乳房X线图像分析协会数据库中的322个乳房X线照片进行开发和评估的。验证结果表明,该技术的灵敏度为94.59%,每张图像的假阳性率为3.90。

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