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Survey on Methods of Tumor Region Detection and Tumor Classification in Mammographic Image


Nehaben V. Chauhan , Sardar Vallabhbhai Patel Institute Of Technology; Jayna B. Shah, Sardar Vallabhbhai Patel Institute Of Technology


Mammograms, Breast Cancer, Enhancement Classifiers, MIAS


At present in Medical science, the reason for the tremendous growth of breast cancer is unknown. Mammography or mammograms play an important role in early detection of breast cancer. Mammography is specialized medical imaging that uses a low-dose x-ray system to see inside the breasts. Digital mammography convert x-rays into mammographic images of the breast. A lump or tumor will show up as a focused white area on a mammogram image. Tumors can be cancerous or benign. Researchers have been emerged many techniques to detect tumor and classify it as cancerous or benign. This survey paper focus on the different techniques on enhancement of mammogram images, detection and classification of breast tumor. In this survey papers, the authors attempt different enhancement techniques such as filtering with morphological operation, Histogram equalization, median filtering, Contrast limited adaptive histogram equalization (CLAHE) to enhance the image. They used various feature extraction methods like GLCM, Gabor filter and DWT to extract features from image. They used various classification methods such as SVM, ANN, BPNN, Bayesian classifier, KNN to classify the image.

Other Details

Paper ID: IJSRDV7I20089
Published in: Volume : 7, Issue : 2
Publication Date: 01/05/2019
Page(s): 274-278

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