Two-Stage Hybrid Convolutional-Transformer Models for Breast Cancer Histopathology.

In this study, we present a two-stage algorithm utilizing hybrid Convolutional-Transformer models, specifically ConvMixer and Coatnet, for breast cancer histopathology image classification. Our methodology focuses on two critical stages: training and mitosis detection. The training stage incorporates advanced color normalization and data augmentation techniques, enhancing the models' ability to process complex histopathological images.