https://github.com/broadinstitute/one-shot-atlas
Siamese Neural Network for anatomical registration
Science Score: 57.0%
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Repository
Siamese Neural Network for anatomical registration
Basic Info
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Metadata Files
README.md
Siamese Neural Network for anatomical registration
In this repository is contained the code of the paper https://www.biorxiv.org/content/10.1101/2020.08.29.272831v1 relative to the registration pipeline. The aim of this model is, given an histology image of a coronal slice of the mouse brain, to identify its "depth" into the brain by comparing it with an existing atlas (e.g. Allen CCF). The model is a Siamese Neural Network based on a pretrained DenseNet encoder of which we fine-tuned the final layers. The model works as depicted in the figure below.
In this repository you can find: - The code used to train the model - A pretrained version of the model itself - A jupyter notebook containing some usage examples
To run the code you need Python >= 3.6 and the following packages installed:
tensorflow > 2.0
numpy
matplotlib
imgaug
pandas
pickle
umap-learn
scipy
You will also need to populate the brain_images folder with the mouse brain samples that can be found at: LINK
To train a new model edit the file main.py with the correct hyperparameters and run the command python main.py.
To test a trained model use the notebook Predictions.ipynb.
Owner
- Name: Broad Institute
- Login: broadinstitute
- Kind: organization
- Location: Cambridge, MA
- Website: http://www.broadinstitute.org/
- Twitter: broadinstitute
- Repositories: 1,083
- Profile: https://github.com/broadinstitute
Broad Institute of MIT and Harvard
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