CLASSIFICATION OF COLORECTAL CANCER USING HISTOPATHOLOGICAL IMAGES BASED ON HYBRID CNN MODEL

This work presents a deep learning-based approach for colorectal cancer image classification using a hybrid CNN and Transformer architecture. The model utilizes CNN for feature extraction and a transformer encoder for capturing contextual relationships. Score-CAM is used to provide visual interpretability of model predictions. The model is trained and validated on a colorectal cancer histopathological image dataset and achieves high classification performance.