Feasibility study for reconstruction of knee MRI from one corresponding X-ray via CNN

Zhe Wang, Aladine Chetouani, Rachid Jennane
3/16/2025
eess.IVcs.CV

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Abstract

Generally, X-ray, as an inexpensive and popular medical imaging technique, is widely chosen by medical practitioners. With the development of medical technology, Magnetic Resonance Imaging (MRI), an advanced medical imaging technique, has already become a supplementary diagnostic option for the diagnosis of KOA. We propose in this paper a deep-learning-based approach for generating MRI from one corresponding X-ray. Our method uses the hidden variables of a Convolutional Auto-Encoder (CAE) model, trained for reconstructing X-ray image, as inputs of a generator model to provide 3D MRI.

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Cite this paper

@article{wang2025feasibility,
  title  = {Feasibility study for reconstruction of knee MRI from one corresponding X-ray via CNN},
  author = {Zhe Wang and Aladine Chetouani and Rachid Jennane},
  year   = {2025},
  eprint = {2503.13555},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2503.13555v1}
}

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