/rsna_heme

Automated detection and classification of intracranial hemorrhage at noncontrast CT

Primary LanguageJupyter NotebookMIT LicenseMIT

README

This package contains tools for training a simple 2D convolutional neural network deep learning model to identify and subclassify acute intracranial hemorrhage at noncontrast CT. Training data come from the RSNA Intracranial Hemorrhage Detection dataset on Kaggle.

Installation

  1. Make sure a version of mxnet is installed with GPU support. For example:

    pip install mxnet-cu92mkl
  2. Download this repository, either with git clone <URL> (where <URL> is the git repository URL) or by clicking the download link in the git web interface.

  3. Install the companion python module. From the command line:

    cd /path/to/unet_brats/
    pip install .
    

    Alternatively, install directly from the git repository like:

    pip install git+https://github.com/johncolby/rsna_heme

Usage

Example Jupyter notebooks for training and testing/inference are included in the notebooks directory.