About this document
SwinIR for Medical Image Super-Resolution by Nusrat Zahan is a document available to read on EtoBox.
This document discusses using the SwinIR Transformer for medical image super-resolution. It evaluates several single image super-resolution architectures, including SRGAN, BSRGAN, RealESRGAN, and SwinIR, on medical images. It finds that SwinIR considerably improves the peak signal-to-noise ratio and structural similarity index compared to other architectures, allowing for more precise medical image analysis and disease identification. Deep learning techniques have become increasingly important for medical i
- Author
- Nusrat Zahan
- Language
- EN