DETECTION OF MAMMOGRAPHIC CANCER USING SUPPORT VECTOR MACHINE AND DEEP NEURAL NETWORK

Authors:

Timmana Hari Krishna,C. Rajabhushnam,

DOI NO:

https://doi.org/10.26782/jmcms.2019.12.00013

Keywords:

Malignant,Image Processing,Support Vector Machine,Feature Extraction,Deep Neural Network,

Abstract

Cancer is a disease which is usually happens among the individuals everywhere throughout the world. There are numerous reasons to happen the malignant growth like as various habitats, environmental disorders and so forth. Cancer growth being identified at beginning periods can saves a large number of peoples, if viable cure is specified. It can make harm any piece of body. Generally the cancer occurs in breast of ladies. When a breast cells divide rapidly, it creates a group of mass which is called tumor . It is very difficult to detect the breast cancer tumor, it is very challenging task. Also the structure of the cancer cells are very complicated. In this article a prediction of breast cancer is present. In this a deep learning support-vector-method (D-SVM) is used to identify the breast cancer tumor. Also, In a early stages of an mammographic cancer a segmentation to threshold method is used. For the classification and for the feature extraction purpose this DSVM method is used. In this method we integrates conventional support vector machine (SVM) & classifier deep-neural-network. Likewise, probability of the lump to differentiate its sort is additionally taken in this paper for example amiable, suspicious or harmful.

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