adalca / Neurite
Licence: apache-2.0
Neural networks toolbox focused on medical image analysis
Stars: ✭ 203
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Neurite
A neural networks toolbox with a focus on medical image analysis in tensorflow/keras for now.
Install
To use the Neurite library, either clone this repository and install the requirements listed in setup.py or install directly with pip.
pip install neurite
Main tools
-
layers: various network layers, sparse operations (e.g.
SpatiallySparse_Dense), andLocallyConnected3Dcurrently not included inkeras -
utils: various utilities, including
interpn: N-D gridded interpolation, and several nonlinearities - models: flexible models (many parameters to play with) particularly useful in medical image analysis, such as UNet/hourglass model, convolutional encoders and decoders
- generators: generators for medical image volumes and various combinations of volumes, segmentation, categorical and other output
-
callbacks: a set of callbacks for
kerastraining to help with understanding your fit, such as Dice measurements and volume-segmentation overlaps - dataproc: a set of tools for processing medical imaging data for preparation for training/testing
- metrics: metrics (most of which can be used as loss functions), such as Dice or weighted categorical crossentropy
- plot: plotting tools, mostly for debugging models
Requirements:
- tensorflow, keras and all of their requirements (e.g. hyp5)
- numpy, scipy, tqdm
- pystrum
Papers:
If you use this code, please cite:
Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation
Adrian V. Dalca, John Guttag, Mert R. Sabuncu
CVPR 2018.
[ PDF | arxiv | bibtex ]
If you are using any of the sparse/imputation functions, please cite:
Unsupervised Data Imputation via Variational Inference of Deep Subspaces
Adrian V. Dalca, John Guttag, Mert R. Sabuncu
Arxiv preprint 2019
[ arxiv | bibtex ]
Development:
Please open an issue [preferred] or contact Adrian Dalca at [email protected] for question related to neurite.
Use/demos:
Parts of neurite were used in VoxelMorph and brainstorm, which we encourage you to check out!
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