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medgen's Introduction

Using generative models to create 3D medical images

Implementation

Pytorch implmentation of a 3D-DDPM and 3DPGGAN

  • DDPM model was able to outperform the 3DPGGAN by a few %
  • Further optimization of the 3DPGGAN is needed to improve performance

Dataset

  • Dataset obtained as part of MMWHS consists of 20 labelled CT scans for training and 40 unlabelled CT scans for testing
  • Images and labels are divided into folders called "/ct_train_images/" and "/ct_train_labels"
  • Originally experimentation was not conditioned on labelled images

Sample Images

  • 2d axial slices obtained from 3D image at resolution of 128 x 128

medgen's People

Contributors

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