660-04-013 ISMRM Abstract

A Cycle-GAN-Based MRI to X-ray and X-ray to MRI Synthesis for the Knee Joint

Primary: Analysis Methods - Image Synthesis and Translation

Secondary: Acquisition & Reconstruction - AI methods

660-04-013 · AI: Anything Synthetic or Correcting Artifacts · Thursday, 14 May, 2:35 PM–3:30 PM · Digital Posters Row A

Keywords: Deep learning Image synthesis Knee Osteoarthritis Cycle Generative Adversarial Network MRI to X-ray

Accepted

Suneeta Chaudhary ¹, Surabhi Thatte¹, Bhushan Borotikar¹

¹Symbiosis Centre for Medical Image Analysis, Symbiosis International University, Pune, India

Presenting Author: Suneeta Chaudhary

Synopsis

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References

1. Goodfellow I, Pouget-Abadie J, Mirza M, et al. Generative adversarial nets. Adv Neural Inf Process Syst. 2014;27:2672–2680.

2. Nie D, Trullo R, Lian J, et al. Medical image synthesis with context-aware generative adversarial networks. Med Image Computing and Comput Assist Interv. 2017;10435:417–425. doi: 10.1007/978-3-319-66179-7_48 [doi]

3. Zhu JY, Park T, Isola P, Efros AA. Unpaired image-to-image translation using cycle-consistent adversarial networks. Proc IEEE Int Conf Comput Vis. 2017;2223–2232. doi: 10.1109/ICCV.2017.244 [doi]

4. Liu Y, Chen A, Shi H, Huang S. CT synthesis from MRI using multi-cycle GAN for head-and-neck radiation therapy. Comput Med Imaging Graph. 2021;91:101953. doi: 10.1016/j.compmedimag.2021.101953 [doi]

5. Stimpel B, Syben C, Würfl T, Mentl K, Dörfler A, Maier A. MR to X-ray projection image synthesis. arXiv preprint arXiv:1710.07498. 2017.

6. Johnson J, Alahi A, Fei-Fei L. Perceptual losses for real-time style transfer and super-resolution. Eur Conf Comput Vis. 2016;9906:694–711. doi: 10.1007/978-3-319-46475-6_43 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/660-04-013