Article

Deepali Kailas Gaikwad, Sandip Institute Of Technology And Research Centre, Nashik; Shruti Kulkarni ,Sandip Institute Of Technology And Research Centre, Nashik; Sapna Morade ,Sandip Institute Of Technology And Research Centre, Nashik; Sampada Deore ,Sandip Institute Of Technology And Research Centre, Nashik

The disease is curable if it is detected in early stage [1][8]. Breast cancer is a malignant tumour that starts in the cells of breast, which is group of cancer cells that grow into surrounding tissues. Breast cancer occurs in human and other mammals also [5]. Mammography is reliable tool for detection breast cancer before clinical symptoms appears in digital mammography which is currently considered as a standard method for breast cancer diagnosis. Various types of features are extracted from digital mammogram like position features, shape features and texture features etc [2]. Feature extraction of an image is important in tumour classification [10]. In proposed method the suspected region is identified using various features as above and segments it into suspected regions and then classifies them into normal and abnormal regions [11]. Seed point detection algorithm used for segmentation followed by region growing using pixel aggregation and Sigm function used to enhance an image [11]. An efficient technique is proposed for early detection of tumour which uses decomposition property of wavelet transform and is subjected to statistical analysis which involves skewness and kurtosis of decomposed image. These helps to determine the depth of tumour.