# Context-Aware Convolutional Neural Network for Grading of Colorectal Cancer Histology Images

## TL;DR

This paper introduces a novel context-aware CNN that processes high-resolution histology images to improve colorectal cancer grading accuracy by incorporating larger spatial context, outperforming traditional patch-based methods.

## Contribution

The paper presents a new framework that encodes local features and aggregates them considering spatial organization, effectively utilizing high-resolution images for better cancer grading.

## Key findings

- Outperforms traditional patch-based approaches by 3.61% in accuracy.
- Effectively incorporates large spatial context in high-resolution histology images.
- Demonstrates improved performance in colorectal cancer grading and breast cancer classification.

## Abstract

Digital histology images are amenable to the application of convolutional neural network (CNN) for analysis due to the sheer size of pixel data present in them. CNNs are generally used for representation learning from small image patches (e.g. 224x224) extracted from digital histology images due to computational and memory constraints. However, this approach does not incorporate high-resolution contextual information in histology images. We propose a novel way to incorporate larger context by a context-aware neural network based on images with a dimension of 1,792x1,792 pixels. The proposed framework first encodes the local representation of a histology image into high dimensional features then aggregates the features by considering their spatial organization to make a final prediction. The proposed method is evaluated for colorectal cancer grading and breast cancer classification. A comprehensive analysis of some variants of the proposed method is presented. Our method outperformed the traditional patch-based approaches, problem-specific methods, and existing context-based methods quantitatively by a margin of 3.61%. Code and dataset related information is available at this link: https://tia-lab.github.io/Context-Aware-CNN