• SAGAR TAWANI
• Dr. AJAY GURJAR

One of the most widely renowned causes for higher death rates among women is Breast cancer. Early detection and care are of extreme importance for lowering the death rate due to breast cancer. Recent developments in digital mammography imaging systems intend to provide a better diagnosis of breast abnormalities. By early detecting the presence of micro-calcification in the mammograms we can diagnose the breast cancer. The proposed research paper is split into three stages to provide a system for classification between cancerous and noncancerous cases. The principle stage is the Segmentation Process, which applies threshold filters to separate the abnormal objects (foreground) from the breast tissue (background). The further stage in this research work is extraction of various features. This stage makes use of the segmented ROI images to extract characteristic features that may help in identifying abnormalities in mammograms. The various features like Histogram, Gray Level Co-occurrence matrix (GLCM) & Color Dominant are extracted from the distinct mammographic images. The final & concluding stage is classification, in which machine learning is used to distinguish the cancerous & noncancerous images. The proposed method have significantly high Sensitivity, Specificity and Accuracy for detecting microcalcifications for the database of 40 images which are taken from mammography unit of Rotary midtown Club Amravati.

Breast cancer, Microcalcifications, Mammography, Histogram, GLCM, Color Dominant.

"Early stage Detection & Classification of Microcalcification Clusters in the Digital mammograms Using Digital Image Processing & SVM classifier", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 8, page no.518-522, August-2020, Available :http://www.jetir.org/papers/JETIR2008064.pdf

"Early stage Detection & Classification of Microcalcification Clusters in the Digital mammograms Using Digital Image Processing & SVM classifier", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 8, page no. pp518-522, August-2020, Available at : http://www.jetir.org/papers/JETIR2008064.pdf