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An evaluation of contrast enhancement techniques for mammographic breast masses

机译:乳腺钼靶造影增强技术的评估

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摘要

The main aim of this paper is to propose a novel set of metrics that measure the quality of the image enhancement of mammographic images in a computer-aided detection framework aimed at automatically finding masses using machine learning techniques. Our methodology includes a novel mechanism for the combination of the metrics proposed into a single quantitative measure. We have evaluated our methodology on 200 images from the publicly available digital database for screening mammograms. We show that the quantitative measures help us select the best suited image enhancement on a per mammogram basis, which improves the quality of subsequent image segmentation much better than using the same enhancement method for all mammograms.
机译:本文的主要目的是提出一套新颖的度量标准,这些度量标准可以在计算机辅助检测框架中测量乳腺摄影图像的图像增强质量,旨在利用机器学习技术自动发现肿块。我们的方法包括一种新颖的机制,可以将建议的指标组合为一个定量指标。我们已经从公开的数字数据库中筛选出的200幅图像中评估了我们的方法,以筛查X线照片。我们表明,定量措施可帮助我们在每个乳房X线照片的基础上选择最合适的图像增强功能,与对所有乳房X线照片使用相同的增强方法相比,它改善了后续图像分割的质量。

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