# Robust reconstruction of cardiac T1 maps using RNNs

## TL;DR

This paper proposes a recurrent neural network approach for fast and robust reconstruction of cardiac T1 maps, addressing limitations of traditional non-linear fitting methods in terms of computational cost and robustness.

## Contribution

The study introduces a novel RNN-based method for cardiac T1 map reconstruction, improving speed and robustness over existing non-linear fitting techniques.

## Key findings

- RNN method achieves faster reconstruction times.
- The approach enhances robustness against noise and artifacts.
- Potential for clinical application in cardiac MRI.

## Abstract

Cardiac magnetic resonance parametric T1 maps are typically reconstructed using non-linear fitting. However this method has limitations due to the high computational cost and robustness. In this study, a recurrent neural network (RNN) is proposed for the robust and fast reconstruction of cardiac T1 maps.