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Pytorch-adaptation of GPU-accelerated StainTool's stain normalization algorithms

Home Page: https://cielal.github.io/torch-staintools/

License: MIT License

Python 100.00%
pytorch reinhard stain-normalization macenko staintools vahadane computational-pathology digital-pathology gpu-acceleration stain-augmentation

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torch-staintools's Issues

Nan values in output

Hello,

First of all, thank you for your work. I am writing you because I'm having a hard time isolating a problem : at some point during my training, the output of the on-the-fly normalization contains Nan Values. I was wondering if that can happen when the normalization reference (used to fit) is contained in the batch of images to normalize ? It doesn't always happen, which is very strange to me. It may be totally unrelated to my problem, but I need to get an answer to this lead

Have a good day

Extend the stain matrices caching to normalizer.

That should vastly improve the efficiency of Vahadane algorithm when on-the-fly normalization is necessary for multiple iterations, e.g., for multiple epochs of downstream deep learning model training.

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