Computer Aided Detection and Extraction of Breast Cancer from Mammogram Images Using Image Segmentation and Classification Approaches
9 Pages Posted: 8 Oct 2019 First Look: Under Review
Breast cancer is becoming one of the most common cancer diseases which is responsible for most number of deaths of human beings all over the world. So, at present, preventing this cancer is becoming quite harder as there are not any type of proper methodologies to treat this disease. So, identification of this disease early is one of the efficient techniques to provide good treatment for better possibility of recovery of this disease. This work's objective is basically extracting the different tumour affected region in mammogram images, which can help the clinical experts for earlier diagnosis of disease and provide some quick decision regarding treatment. Here in these methods, we combine several techniques for finding cancerous region in the affected image. So, the extracted region is taken from original gray image using image segmentation approach. Here, the primary detection allows the experts to suggest the nature of disease as normal, benign and the malignant type of disease present or not. The results provide better computational time and good statistical parameter of analysis for entire segmentation work. Thus, the process yields good accuracy rates of more than 90% for efficient detection and diagnosis of diseases.
Keywords: Image Processing, Mammography, Preprocessing, Mean, Entropy, Benign, Median Filtering, Classification
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