Assessment of Spatial-variant Noise Level in Real-time Dynamic MR Images - a Random Matrix Approach

TL;DR

This paper introduces a novel random matrix theory-based method for accurately measuring spatially varying noise levels in real-time dynamic MR images, validated through simulations and in-vivo cardiac imaging.

Contribution

The paper presents a new approach leveraging random matrix theory to improve noise level estimation in dynamic MR images, addressing limitations of existing methods.

Findings

Accurately estimates spatial noise variation in dynamic MR images.

Validated method with numerical simulations and in-vivo cardiac MR data.

Demonstrates improved noise assessment over traditional techniques.

Abstract

Accurate measurement of spatially variant noise in dynamic magnetic resonance (MR) images acquired using parallel imaging methods is problematic. We propose a new method based on the random matrix theory to accurately assess the noise level. The method is validated using numerical simulation and in-vivo dynamic cardiac MR images.