Curvelet and PNN classifier based approach for early detection and classification of breast cancer in digital mammograms
Anu Appukuttan, L Sindhu · 2016
Breast Cancer is the most common incursive cancer which is found in females all through the world. of all the female cancers it comprises of 16% and it accounts for 22.9% of invasive cancer in women. of all the cancer deaths 18.2% are from breast cancer which includes males and females. As the modern science is improving many researches and techniques have been emerged to eradicate this dreadful disease. So there is a need of an automated computer aided diagnosis system and it is proposed here. This paper proposes a method to detect microcalcifications and circumscribed masses and also classify them as benign and malignant. For this a curvelet and texture analysis are used for feature extraction and PNN classifier is used for classification. The proposed method is evaluated using Mini Mammographic Image Analysis Society(Mini-MIAS) dataset and an accuracy of 93% has been obtained.