Kaminyou/Kernelized-Instance-Normalization
[ECCV 2022] Official implementation of "Ultra-high-resolution unpaired stain transformation via Kernelized Instance Normalization"
This project helps pathologists and medical researchers transform ultra-high-resolution images of stained tissue samples. You provide an image stained with one chemical (e.g., Hematoxylin and Eosin) and it outputs an image that appears to be stained with another (e.g., Estrogen Receptor), enabling new insights without needing to restain or acquire new samples. It's designed for professionals working with microscopic pathology slides.
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Use this if you need to digitally convert a high-resolution microscopic image stained with one reagent to appear as if it were stained with a different reagent, without physically re-staining the sample.
Not ideal if you are looking for the absolute latest version of this technology, as the developers recommend a newer method, or if you are working with standard resolution images.
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Language
Python
License
MIT
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Last pushed
Oct 12, 2024
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