# Complex extension of optical flow and its practical evaluation for undersampled dynamic MRI

arXiv: https://arxiv.org/abs/2412.12711 · HTML: https://mlsanity.com/paper/2412.12711/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Dec 2024.

## Built on by (most cited first, 1 of 1)

- [Flow-Guided Implicit Neural Representation for Motion-Aware Dynamic MRI Reconstruction](https://mlsanity.com/paper/2511.16948/) (2025)

## Abstract (arXiv)

Reconstructing high-quality images from undersampled dynamic MRI data is a challenging task and important for the success of this imaging modality. To remedy the naturally occurring artifacts due to measurement undersampling, one can incorporate a motion model into the reconstruction so that information can propagate across time frames. Current models for MRI imaging are using the optical flow equation. However, they are based on real-valued images. Here, we generalise the optical flow equation to complex-valued images and demonstrate, based on two real cardiac MRI datasets, that the new model is capable of improving image quality.