Open AccessSTATISTICAL DETECTION OF BREAST CANCER BY MAMMOGRAM IMAGE
Author(s) -
Shaik Naseera,
G. K. Rajini,
M. Saravanan
Publication year - 2016
Publication title -
asian journal of pharmaceutical and clinical research
Language(s) - English
Resource type - Journals
eISSN - 2455-3891
pISSN - 0974-2441
DOI - 10.22159/ajpcr.2017.v10i1.15003
Subject(s) - breast cancer , skewness , mammography , medicine , standard deviation , statistical analysis , artificial intelligence , perimeter , stage (stratigraphy) , cancer , radiology , pattern recognition (psychology) , computer science , statistics , mathematics , paleontology , geometry , biology
Objective: To create awareness about the breast cancer which has become one of the most common diseases among women that leads to death if notrecognized at early stage.Methods: The technique of acquiring breast image is called mammography and is a diagnostic and screening tool to detect cancer. A cascade algorithmbased on these statistical parameters is implemented on these mammogram images to segregate normal, benign, and malignant diseases.Results: Statistical features - such as mean, median, standard deviation, perimeter, and skewness - were extracted from mammogram images todescribe their intensity and nature of distribution using ImageJ.Conclusion: A noninvasive technique which includes statistical features to determine and classify normal, benign, and malignant images are identified.Keywords: Breast cancer, Benign, Malignant, Mammogram image, ImageJ.