Code for Residual and Plain Convolutional Neural Networks for 3D Brain MRI Classification paper
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jupyter Init Nov 25, 2016
scripts Init Nov 25, 2016
test_scripts Init Nov 25, 2016
.gitignore Init Nov 25, 2016
.theanorc Init Nov 25, 2016
Dockerfile Update Dockerfile Jun 20, 2017
README.md Update README.md Jan 25, 2017

README.md

Residual and Plain Convolutional Neural Networks for 3D Brain MRI Classification

https://arxiv.org/abs/1701.06643

Authors: Sergey Korolev, Amir Safiullin, Mikhail Belyaev, Yulia Dodonova


Scripts for training without Docker image are located in scripts folder


Install docker-jupyter

Install Docker https://docs.docker.com/engine/installation/

Install nvidia-docker https://github.com/NVIDIA/nvidia-docker/wiki/Installation

Howto run docker-jupyter

Clone:

git clone https://github.com/neuro-ml/resnet_cnn_mri.git

cd resnet_cnn_mri

Build:

[sudo] docker build -t dl_isbi:repr -f Dockerfile .

Run container:

[sudo] nvidia-docker run -it -p 8809:8888 -v ~/absolute/path/to_data:/scripts/data/ dl_isbi:repr bash

where ~/absolute/path/to_data is absolute path on your local machine to folder with adni data.

Run notebook inside the container:

jupyter notebook

Open http://localhost:8809 on your local machine.


Data

Place all the .nii files and metadata.csv inside ~/absolute/path/to_data (on your local machine).

metadata.csv should have Label and Path columns for file retrieval and class labels (you can find sample /scripts/data/metadata.csv). Path value shoult be data/some/path/to_scan.nii