DETECTION OF MALIGNANT TUMOUR IN MAMMOGRAPHY IMAGES USING ADAPTIVE CLUSTERING SEGMENTATION
DOI:
https://doi.org/10.24297/jac.v12i26.1985Keywords:
Pre-processing, adaptive clustering segmentation, threshold comparison, accuracy and breast cancer detection.Abstract
The group of cancer cells that initiate from the breast cells and it expands from tissue of breast and leads to breast cancer. To identify the breast cancer Mammogram is one of the efficient techniques used now days in earlier using x-ray images of breast and this will reduce the death ratio of breast cancer patients. A new approach is implemented to detect the breast cancer of women by its image and it is discussed in this paper. Initially, pre-processing is applied which converts the original image into gray scale and adaptive clustering segmentation is implemented. Based on segmented image feature is extracted and compared with normal patient image. Normal patient parameters are taken and considered as threshold value and processed patient value is compared to identify the abnormal patient. Hence the accuracy of proposed approach is measured by the factors like Sensitivity, Specificity and Accuracy. Hence it shows that proposed works obtains better detection of cancer when compared to other existing methods.Â
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All articles published in Journal of Advances in Linguistics are licensed under a Creative Commons Attribution 4.0 International License.
