Author : Madhumati U. Kavale and Prof. Nagaraju Bogiri

Breast Cancer is amongst the most fatal and highly aggressive form of cancer for females. This is one of the critical diagnosis that can be effective if performed in due time. The majority of the breast cancer related deaths that are happening across the world are mostly due to the late diagnosis of the cancer. The slower diagnostic interventions can allow the breast cancer cells to metastasize which can lead to an increased spread of the cancer cells. This can lead to further complications and can be difficult to prevent the untimely demise of the patient. Therefore, there is a need for an effective and timely diagnosis of the breast cancer for which the CT scan images are utilized. The manual analysis of these images is highly cumbersome and can take a large amount of time which is not the most effective strategy as it can be quite detrimental to the patient. Thus, this research article is tasked with the realization of the breast cancer detection in CT images through the use of image processing methodologies. The presented approach trains a Convolutional Neural Network along with the implementation of Decision making to perform the identification of the Breast cancer in CT images which leads to a drastic improvement in the detection accuracy. The experimental evaluation has been performed using the confusion matrix with satisfactory results for the breast cancer identification accuracy.

Keywords: Breast CT images, Convolutional Neural Network, Decision Making