Pre- to Post-Contrast Breast MRI Synthesis for Enhanced Tumour Segmentation

In SPIE Medical Imaging 2024.

Getting Started

The Duke Dataset used in this study is available on The Cancer Imaging Archive (TCIA).

You may find some examples of synthetic nifti files in synthesis/examples.

Synthesis Code

• Config to run a training of the image synthesis model.
• Config to run a test of the image synthesis model.
• Code to transform Duke DICOM files to NiFti files.
• Code to extract 2D pngs from 3D NiFti files.
• Code to create 3D NiFti files from axial 2D pngs.
• Code to separate synthesis training and test cases.
• Code to compute the image quality metrics such as SSIM, MSE, LPIPS, and more.
• Code to compute the Frèchet Inception Distance (FID) based on ImageNet and RadImageNet.

Segmentation Code

• Code to prepare 3D single breast cases for nnunet segmentation.
• Train-test-splits of the segmentation dataset.
• Script to run the full nnunet pipeline on the Duke dataset.

Acknowledgements

This repository borrows code from the pix2pixHD and the nnUNet repositories. The 254 tumour segmentation masks used in this study were provided by Caballo et al.