Application of deep learning models in the pathological classification and staging of esophageal cancer: A focus on Wave-Vision Transformer

Figure 5 Wavelets module of the Wave-Vision Transformer model. This figure visually illustrates the Wavelets module’s structure and functionality within the Wave-Vision Transformer model. The module is designed to leverage wavelet transform for multi-scale feature extraction while preserving information integrity. By integrating wavelet transform with self-attention mechanisms, Wave-Vision Transformer achieves lossless downsampling, effectively retaining high-frequency information such as textures and edges, which enhances the model’s sensitivity to fine details. DWT: Discrete wavelet transform.