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Breast cancer detection using non-invasive method for real time dataset

机译:使用非侵入性方法检测乳腺癌的实时数据集

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Breast Cancer is one of the most horrible and dangerous diseases that affect women health. This paper aims to detect the breast cancer in a non-invasive manner with the help of mammograms and enables advanced characterization of the lesion using following steps: mammogram enhancement using adaptive median filter, cancer area detection using seed value based segmentation, extraction of CSLBP and GLDM features and finally, classification of cancer using RBF-SVM. The Algorithm is evaluated on real time mammogram breast dataset consisting of 249 images and for the considered dataset, accuracy is found to be 95.18%.
机译:乳腺癌是影响妇女健康的最恐怖,最危险的疾病之一。本文旨在借助乳房X线照片以无创方式检测乳腺癌,并通过以下步骤实现病变的高级表征:使用自适应中值滤波增强乳房X线照片,使用基于种子值的分割来检测癌变区域,提取CSLBP和GLDM的特点是使用RBF-SVM对癌症进行分类。该算法在由249张图像组成的实时乳房X线照片乳房数据集上进行评估,发现该数据集的准确性为95.18%。

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