This is a super-resolution algorithm for pathology. The program runs on the mmcv_full==1.6.0 library.
Here is the code for the manusript:  Accurate diagnosis achieved via super-resolution whole slide images by pathologists and artificial intelligence
with the doi: https://medrxiv.org/cgi/content/short/2024.07.05.24310022v1.

(1) Dataset:
A minimized MSR training and validation dataset, from which 10% of images were randomly sampled for each.
Download link:https://pan.baidu.com/s/1Uu0P-NFX9W6NXlVGcvLA4g?pwd=g33c

(2) Modify configs/restorers/Pathology_MSR/glean_in256out2048_pathology.py:
Update paths in the data dictionary for the dataset:
lq_folder='your path'
gt_folder='your path'
Set other hyperparameters inside as needed, including loss functions, number of iterations, etc.

(3) configs/restorers/Pathology_MSR/create_anno.py:
Select a subset of images from the validation set for validation (to reduce validation time) and generate the create_anno.txt file.

(4) tools/train.py: Train the MSR model.
Requires a Tesla A100 80GB GPU, approximately 3-4 days depending on the number of iterations.

(5) demo/restoration_demo.py: Generate a 40X image from a 5X image for demonstration.

(6) tools/generate_WSI.py: Generate 40X whole slide images from 5X image patches.

(7) Pretrained models:
pretrained/finetuned-style-gan.pth: The finetuned StyleGAN model for pathology images.
pretrained/pretrained_MSR.pth: A pretrained MSR model.
Download link: https://pan.baidu.com/s/1KXqGceto7GhH3f02RzjnXQ?pwd=qdax