Histopathology Magnification Generalization

The code for magnification generalization for the histopathology image embedding

This is the code for the paper:

• Milad Sikaroudi*, Benyamin Ghojogh*, Fakhri Karray, Mark Crowley, H.R. Tizhoosh, "Magnification Generalization for Histopathology Image Embedding", IEEE International Symposium on Biomedical Imaging (ISBI), 2021.

Link of arXiv version of paper: https://arxiv.org/abs/2101.07757v1

This code/paper uses Model Agnostic Semantic Features (MASF) for the maginification generalization in histopathology image embedding. The paper of MASF is:

• Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Ben Glocker, "Domain generalization via model-agnostic learning of semantic features." In Advances in Neural Information Processing Systems, pp. 6450-6461, 2019.

The code of MASF method can be found in the following link: https://github.com/biomedia-mira/masf

The MASF method, itself, is inspired by Model Agnostic Meta-Learning (MAML) whose paper is:

• Chelsea Finn, Pieter Abbeel, Sergey Levine. "Model-agnostic meta-learning for fast adaptation of deep networks." In International Conference on Machine Learning, pp. 1126-1135, 2017.

The tensorflow code of MAML method can be found in the following two links: https://github.com/cbfinn/maml and https://github.com/siavash-khodadadeh/UMTRA-Release