Color-cadx: A Deep Learning Approach For Colorectal Cancer Classification Through Triple Convolutional Neural Networks And Discrete Cosine Transform

This article discusses the use of computer-aided diagnostic systems, specifically the proposed “Color-CADx,” for the recognition of colorectal cancer (CRC). The system utilizes deep learning algorithms and features extracted from different convolutional neural networks, which are then reduced using discrete cosine transform and analyzed using ANOVA. The system achieved high accuracy rates on two publicly available datasets, demonstrating its efficacy in aiding pathologists with CRC diagnosis.