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Multi-Contrast MRI Segmentation Trained on Synthetic Images

Image and Video Processing 2022-07-07 v1 Computer Vision and Pattern Recognition Machine Learning

Abstract

In our comprehensive experiments and evaluations, we show that it is possible to generate multiple contrast (even all synthetically) and use synthetically generated images to train an image segmentation engine. We showed promising segmentation results tested on real multi-contrast MRI scans when delineating muscle, fat, bone and bone marrow, all trained on synthetic images. Based on synthetic image training, our segmentation results were as high as 93.91\%, 94.11\%, 91.63\%, 95.33\%, for muscle, fat, bone, and bone marrow delineation, respectively. Results were not significantly different from the ones obtained when real images were used for segmentation training: 94.68\%, 94.67\%, 95.91\%, and 96.82\%, respectively.

Keywords

Cite

@article{arxiv.2207.02469,
  title  = {Multi-Contrast MRI Segmentation Trained on Synthetic Images},
  author = {Ismail Irmakci and Zeki Emre Unel and Nazli Ikizler-Cinbis and Ulas Bagci},
  journal= {arXiv preprint arXiv:2207.02469},
  year   = {2022}
}

Comments

IEEE EMBC 2022 conference (oral) paper

R2 v1 2026-06-24T12:15:28.570Z