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minc_keras is a code base that was developped during a hackathon to facillitate the implementation of deep learning models for brain imaging with the Keras package.

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minc_keras

About

minc_keras is a code base that was developped during a hackathon to facillitate the implementation of deep learning models for brain imaging with the Keras package.

Google Colab

Create / Log-in to Google account
Go to https://colab.research.google.com
Download and load: https://tinyurl.com/yd8dd5x3\

Presentations

NeurotechMTL -- Deep Learning with MRI (3.21.18)
NeurotechMTL -- Intro to ML (3.21.18)

Installation

Docker (very easy):

Install docker on your OS: https://docs.docker.com/install/#cloud

docker pull tffunck/neurotech:latest

DIY (pretty easy):

wget https://bootstrap.pypa.io/get-pip.py (Or go to the link and download manually)

python3 get-pip.py

pip3 install pandas numpy scipy h5py matplotlib tensorflow keras

git clone https://github.com/tfunck/minc_keras

Data

Data should be organized in the BIDS format (http://bids.neuroimaging.io/). While the code in this repository is in theory supports HDF5 files, at the moment only the MINC format is supported. Nifti support will be provided in future releases.

Example Data :

data/output/

data/output/sub-01/sub-01_task-01_ses-01_T1w_anat_rsl.mnc

data/output/sub-01/sub-01_task-01_ses-01_variant-seg_rsl.mnc

data/output/sub-02/sub-02_task-01_ses-01_T1w_anat_rsl.mnc

data/output/sub-02/sub-02_task-01_ses-01_variant-seg_rsl.mnc

Useage

Basic Useage:

python3 minc_keras/minc_keras.py --source /path/to/your/data/ --target /path/to/desired/output --epochs --input-str "string that identifies input files" --label-str "string that identifies labeled files" --predict

Example:

python3 minc_keras/minc_keras.py --source minc_keras/data/output/ --target . --epochs 5 --input-str "T1w_anat" --label-str "seg" --predict 1

Authors

Thomas Funck ([email protected])

Paul Lemaitre

Andrew Doyle

About

minc_keras is a code base that was developped during a hackathon to facillitate the implementation of deep learning models for brain imaging with the Keras package.

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