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Automatic Diagnosis of Breast Cancer using Thermographic Color Analysis and SVM Classifier

机译:使用热敏颜色分析和SVM分类器自动诊断乳腺癌

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Breast cancer is the commonly found cancer in women. Studies show that the detection at the earliest can bring down the mortality rate. Infrared Breast thermography uses the temperature changes in breast to arrive at diagnosis. Due to increased cell activity, the tumor and the surrounding areas has higher temperature emitting higher infrared radiations. These radiations are captured by thermal camera and indicated in pseudo colored image. Each colour of thermogram is related to specific range of temperature. The breast thermogram interpretation is primarily based on colour analysis and asymmetry analysis of thermograms visually and subjectively. This study presents analysis of breast thermograms based on segmentation of region of interest which is extracted as hot region followed by colour analysis. The area and contours of the hottest regions in the breast images are used to indicate abnormalities. These features are further given to ANN classifier for automated analysis. The results are compared with doctor's diagnosis to confirm that infra-red thermography is a reliable diagnostic tool in breast cancer identification.
机译:乳腺癌是女性常见的癌症。研究表明,最早的检测可以降低​​死亡率。红外乳房热成像使用乳房的温度变化来诊断。由于细胞活性增加,肿瘤和周围区域具有较高的红外辐射温度。这些辐射被热摄像机捕获并在伪彩色图像中指示。热分析点的每种颜色与特定的温度范围有关。乳房热法理解释主要基于视觉和主观热视图的颜色分析和不对称性分析。本研究介绍了基于感兴趣区域的分割的乳房热量点分析,其提取为热区域,然后进行颜色分析。乳房图像中最热区域的区域和轮廓用于表示异常。这些特征进一步给了ANN分类器,用于自动分析。结果与医生的诊断进行了比较,以确认红外热成像是乳腺癌鉴定中可靠的诊断工具。

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