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

arXiv: https://arxiv.org/abs/2503.13555 · HTML: https://mlsanity.com/paper/2503.13555/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 3 references that are in the map.
- First posted on arXiv 16 Mar 2025.

## Builds on (most cited first, 1 of 1)

- [Diagnostic Classification Of Lung Nodules Using 3D Neural Networks](https://mlsanity.com/paper/1803.07192/) (2018)

## Abstract (arXiv)

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.