# Review: Noise and artifact reduction for MRI using deep learning

arXiv: https://arxiv.org/abs/2002.12889 · HTML: https://mlsanity.com/paper/2002.12889/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Feb 2020.

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

- [Improved 3D Whole Heart Geometry from Sparse CMR Slices](https://mlsanity.com/paper/2408.07532/) (2024)

## Abstract (arXiv)

For several years, numerous attempts have been made to reduce noise and artifacts in MRI. Although there have been many successful methods to address these problems, practical implementation for clinical images is still challenging because of its complicated mechanism. Recently, deep learning received considerable attention, emerging as a machine learning approach in delivering robust MR image processing. The purpose here is therefore to explore further and review noise and artifact reduction using deep learning for MRI.