An Efficient Colorectal Cancer Detection Network Using Atrous Convolution With Coordinate Attention Transformer And Histopathological Images

A new deep learning network, CCDNet, has been developed to improve the accuracy and efficiency of colorectal cancer diagnosis using histopathology images. The network utilizes a Wiener based Midpoint weighted non-local means filter for denoising and data augmentation to prevent overfitting. The proposed AConvCAT framework, consisting of four modules, is used for categorization of colorectal tissues. This network has the potential to significantly enhance CRC detection rates.