Colon Cancer Classification using Google Net

Colon cancer is a general form of avoidable cancer, which is also widely spread across the globe. It is also a leading cancer and considered as big killer among all kinds of cancers. In recent times, significant advances are developed in treatment field of this frequently causing disease. There are several traditional techniques which are not flexible, robust and time consuming as they are devised for manual assessment of colon cancer. In this work, pre-processing is conducted utilizing median filter for removing noises from an input colon cancer image. The filtered image is then segmented using SegNet, which is utilized to segment the affected portions. Finally, classification of colon cancer is conducted employing various deep learning approaches like CNN and GoogLeNet. The comparative assessment showed GoogLeNet as the best classifier for colon cancer classification.