实时数据集的非侵入性乳腺癌检测方法

2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI) Pub Date : 2016-09-01 DOI:10.1109/ICACCI.2016.7732124

Basavaraj Hiremath, S. Prasannakumar, K. Praneethi

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引用次数: 0

摘要

乳腺癌是影响女性健康的最可怕、最危险的疾病之一。本文旨在借助乳房x线照片无创检测乳腺癌，通过以下步骤对病变进行高级表征: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检测肿瘤区域，提取CSLBP和GLDM特征，最后使用RBF-SVM对肿瘤进行分类。该算法在包含249张图像的实时乳房x线照片数据集上进行了评估，对于所考虑的数据集，准确率为95.18%。

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

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%.

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2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

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