cwlkr/torchvahadane
Gpu accelerated vahadane stain normalization for Digital Pathology workflows.
This tool helps pathology researchers and scientists standardize the appearance of tissue slide images before analysis. It takes in digital pathology images with varying stain characteristics and outputs normalized images, ensuring consistent color and intensity across different samples or batches. This is crucial for training reliable AI models or for consistent visual interpretation by pathologists.
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Use this if you are working with digital pathology images and need to ensure consistent stain appearance across different slides or batches, especially for deep learning model development or comparative analysis.
Not ideal if you are not working with digital pathology images or do not require stain normalization for your image analysis tasks.
Stars
27
Forks
5
Language
Python
License
MIT
Category
Last pushed
Feb 23, 2024
Commits (30d)
0
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