Evaluation of Multi-Modal MRI Images for Brain Tumor Segmentations

This is an implementation of evaluation of MRI modalities for the segementation of brain tumors with use of UNET using keras and python. For more details read this paper Multi-Modal MRI Images for Brain Tumor Segmentations.

Installation

Clone the GitHub repository and install the dependencies.

• Install

  • Anaconda (for creating and activating a separate environment)
  • numpy=1.13.3
  • matplotlib
  • scikit-learn==0.19.1
  • Tensorflow==1.1.8

• Clone the repo and go to the directory

$ git clone https://github.com/SafiaFatima/brats2015.git
$ cd brats2015

Preprocessing

For the preprocessing of the images, applying different filters you can simply change the settings in data_prep_noaug.py

For preprocessing of the dataset :

python data_prep_noaug.py

Training

The pretrained model is saved in models/ directory. Once you get the concept of upsampling & downsampling, you can train your own model by changing the setting in training.py.

For training the model use :

python training.py

Testing

Testing of a trained model can be simply done by running:

python testing.py

Credits

This work is done under the supervision of Dr. Hafeez Ur Rehman.