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Masked Diffusion Models to Predict Morphological Relationships from Brain MRI.

Project Structure

├── README.md                   # Project description
├── environment.yml             # Conda environment file
├── Makefile                    # File with directives for the `make` tool
├── setup.py                    # Build script for setuptools
├── data
│   ├── interim                 # Interim data
│   ├── raw                     # Raw data
│   └── transformed             # Processed data
├── masked_diffusion            # Project working files
│   ├── etl                     # Scripts for extracting, transforming, and loading data
│       ├── __init__.py
│       ├── custom_dataset.py   # Data processing script
│       ├── data_utils.py       # Data utility functions
│       ├── image_utils.py      # Image utility functions
│       ├── ixi_data_module.py  # Training dataset loading script
│       ├── preprocess_mri.py   # MRI preprocessing script
│       └── slice_extractor.py  # MRI slice extraction script
│   ├── model                   # Scripts for model training and evaluation
│       ├── __init__.py
│       ├── train.py            # Training script
│       ├── model.py            # Diffusion model implementation script
│       ├── inpaint.py          # Inference script
│       ├── repaint.py          # RePaint algorithm script
│       └── config.yml          # Configuration file
│   ├── __init__.py    
│   └── utils.py                # Utility functions       
└── notebooks                   # Jupyter notebooks for exploration and presentation

Download Pre-trained Model

The model parameters can be downloaded from here. Please put them into masked_diffusion/model/pretrained.

MRI Preprocessing

Prior to applying our trained model to your MRI data, it's crucial to undergo specific preprocessing steps. Note: Before running the script make sure to perform skull-stripping and registration using FreeSurfer or a similar MRI processing tool (following this procedure).

make preprocess_mri DATA_PATH="/your_subj_path" SAVE_DIR="/save_dir_path" PREPROCESS_ARGS="--offset 15"

Tumour Inpainting

You can download the weights for the model using:

make get_weights SAVE_DIR="--path /save_dir_path"

To perform MRI image inpainting run the following command on a .mgz MRI file obtained from MRI preprocessing step.

make inpaint DATA_PATH="/your_subj_path" WEIGHTS_PATH="/weights_folder_path" SAVE_DIR="/save_dir_path" INPAINT_ARGS="--batch_size 1 --num_inference_steps 250 --jump_length 10 --jump_n_sample 10" GPU_ID=0

NOTE: For both preprocessing and inpainting, the t1 image and tumour mask files in SAVE_DIR should be in .mgz format (can be obtained using FreeSurfer's mri_convert) and be named as follows: t1.mgz, mask.mgz.