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Unified Preprocessing and Enhancement Technique for Mammogram Images

机译:乳房X光图像统一预处理和增强技术

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摘要

In developed countries, breast cancer is one of the foremost reasons for the increase in mortality among women. Microcalcifications in breast tissue are one of the key indications appraised by the radiologist for identification of breast cancer in its early stage. To identifying such microcalcification, masses and architectural distortion in breast preprocessing in mammogram plays a vital role. Additional imaging provides bit more information than an initial screening, and more focus is made to the sceptical masses. For this cause, preprocessing of mammogram images is essential in the process of breast cancer examination as it could reduce the rate of false positive. Prior diagnosis of cancer and other abnormalities in human breast, digital mammogram has appeared as the most accepted screening approach. This manuscript presents contrast enhancement, by using the contrast limited adaptive histogram equalization (CLAHE) and thresholding methods for detecting the breast tumor boundaries from digital mammogram. The proposed techniques were applied in the MIAS database, which contains 322 mammogram images. The breast enhancement and segmentation technique by using thresholding provides promising results. To compare the performance of the studies, contrast improvement index (CII) is used as a performance evaluation parameter.
机译:在发达国家,乳腺癌是女性死亡率增加的原因之一。乳腺组织中的微钙剂是放射科学家评估的关键适应症之一,以在其早期鉴定乳腺癌。为了识别乳房X线图中的乳房预处理中的这种微钙化,群众和架构畸变起着至关重要的作用。附加成像提供比初始筛选更多的信息,并且对持怀疑群体进行更多的焦点。对于这种原因,乳腺图像图像的预处理在乳腺癌检查过程中是必不可少的,因为它可以降低假阳性的速率。在癌症和人类乳房的其他异常的事先诊断,数字乳房X光检查出现了最受欢迎的筛选方法。该稿件通过使用对比度有限的自适应直方图均衡(CLAHE)和用于检测来自数字乳房X线照片的乳腺肿瘤边界的阈值方法来提高对比度增强。所提出的技术应用于MIS数据库,其中包含322个乳房图图像。使用阈值化的乳房增强和分割技术提供了有希望的结果。为了比较研究的性能,对比度改善指数(CII)用作性能评估参数。

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