Novel multiphase contouring and force calculation algorithm for ROI detection and calculation of energy value in multiple scale and orientation for early detection of stages of breast cancer

Abstract

A novel MCFC algorithm has been developed to perform detection of ROI. Detected malignant tumors were processed using a novel approach to identify stages of breast cancer. Preprocessing phase aids in enhancement and noise removal. Preprocessed image is segmented using the MCFC algorithm to detect the ROI that aided in achieving robust segmentation at very low computation time. Combination of wavelet and textural features were used to train the artificial neural network for classification. Tumour stage is identified using a novel approach of calculating the energy values in four different scales and six orientations for each scale. Total of 24 energy values are used for training. System performance was tested on 45 real time patients mammographic images obtained from hospitals. Detection of malignant tumour and its stages was verified by experts in medical field. Overall accuracy obtained is 97% for MIAS images and 90% for real time mammographic images.