A REVIEW ON BREAST CANCER DETECTION USING ARTIFICIAL NEURAL NETWORK

Authors

  • B.Ramya Assistant Professor Department of Computer Applications Dr N.G.P Arts and Science College, Coimbatore Tamil Nadu, INDIA

Keywords:

Artificial Neural Network (ANN), GLCM, Intensity based features, Digital Mammograms, Wavelet transform

Abstract

The Breast Cancer disease is curable if detected in early stage. Screening is carried out on the basis of mammogram; this is used in x-ray image to reveal lumps in the breast. Calcium deposit can also indicate the existence of a tumor in breast. The breast Tumor are of two types first is Benign and second is Malignant, Benign Tumor which is non-cancerous and not life threatening and Malignant Tumor are cancerous and life threatening. Mammography is proven as efficient tool to detect breast cancer before clinical symptoms appears digital mammography is currently considered as standard procedure for breast cancer diagnosis, various artificial intelligence techniques are used for classification problems in the area of medical diagnosis.  This paper presents a research on breast cases of 68 samples proven breast tumor are analyzed and classified into benign and malignant categories using ANN. Two different feature extraction methods GLCM and Intensity based features are explained here.

References

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Additional Files

Published

15-06-2017

How to Cite

B.Ramya. (2017). A REVIEW ON BREAST CANCER DETECTION USING ARTIFICIAL NEURAL NETWORK. International Education and Research Journal (IERJ), 3(6). Retrieved from https://ierj.in/journal/index.php/ierj/article/view/1118