数字乳房x光图像中计算机辅助质量检测的模糊推理系统设计

Volkan Goreke, E. Uzunhisarcikli, B. Oztoprak
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引用次数: 1

摘要

乳腺癌是女性中最常见的癌症。乳房x光检查是用极低水平的辐射对乳房进行x光检查。人工智能和模糊推理技术可以应用于CAD系统。这些系统通常有两个主要阶段,它们的名字是图像处理和分类。在本研究中,我们使用了MIAS数据库中获得的乳房x光片图像。利用图像处理技术和静态特征设计了模糊推理系统。对该系统进行了测试,灵敏度为98%,特异度为99%。该研究结果优于我们先前使用人工神经网络的研究,其灵敏度和特异性分别为% 96%和% 96%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A fuzzy inference system design for computer aided mass detection in digital mammogram images
Breast cancer is the most common cancer in women. A mammogram is an X-ray of the breast, using very low levels of radiation. Artificial intelligence and fuzzy inference techniques can be used in CAD systems. These systems generally have main phases that the their names are image processing, and classification. In this study, we used images of mammogram that were obtained MIAS database. The fuzzy inference system was designed using image processing tecniques and statical features. The system was tested and for sensitivity and Specificity respectively, %98 and %99 was found. This study gave better results than our earlier studies using artificial neural network that have %96 sensivity and %96 specifity.
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