Literature DB >> 12743522

[Accuracy of signal-to-noise ratio measurement method for magnetic resonance images].

Akio Ogura1, Akira Miyai, Fumie Maeda, Hiroyuki Fukutake, Rikiya Kikumoto.   

Abstract

The signal-to-noise ratio (SNR) of a magnetic resonance image is a common measure of imager performance. However, evaluations for the calculation of the SNR use various methods. A problem with measuring SNR is caused by the distortion of noise statistics in commonly used magnitude images. In this study, measurement accuracy was compared among four methods of evaluating SNR according to the size and position of regions of interest (ROIs). The results indicated that the method that used the difference between two images showed the best agreement with the theoretical value. In the method that used a single image, the SNR calculated by using a small size of ROI showed better agreement with the theoretical value because of noise bias and image artifacts. However, in the method that used the difference between two images, a large size of ROI was better in reducing statistical errors. In the same way, the methods that used air noise and air signal were better when applied to a large ROI. In addition, the image subtraction process used to calculate pixel-by-pixel differences in images may reach zero on a minus pixel value when using an image processor with the MRI system and apparatuses associated with it. A revised equation is presented for this case. It is important to understand the characteristics of each method and to choose a suitable method carefully according to the purpose of the study.

Mesh:

Year:  2003        PMID: 12743522     DOI: 10.6009/jjrt.kj00003174111

Source DB:  PubMed          Journal:  Nihon Hoshasen Gijutsu Gakkai Zasshi        ISSN: 0369-4305


  6 in total

1.  Measuring signal-to-noise ratio in partially parallel imaging MRI.

Authors:  Frank L Goerner; Geoffrey D Clarke
Journal:  Med Phys       Date:  2011-09       Impact factor: 4.071

Review 2.  Diffusion Tensor Imaging of TBI: Potentials and Challenges.

Authors:  David B Douglas; Michael Iv; Pamela K Douglas; Ariana Anderson; Sjoerd B Vos; Roland Bammer; Michael Zeineh; Max Wintermark
Journal:  Top Magn Reson Imaging       Date:  2015-10

3.  Magnetic resonance thermal imaging combined with SMASH navigators in the presence of motion.

Authors:  Youngseob Seo; Jacob Willig-Onwuachi; Jeffrey H Walton
Journal:  J Appl Clin Med Phys       Date:  2012-07-05       Impact factor: 2.102

4.  Optimization of scan protocol for high temporal resolution magnetic resonance imaging of the liver under single breath-holding using compressed sensing and parallel imaging techniques in a 1.5-T magnetic resonance system.

Authors:  Fumiaki Fukamatsu; Akira Yamada; Hayato Hayashihara; Yoshihiro Kitou; Yasunari Fujinaga
Journal:  BJR Open       Date:  2021-11-24

5.  Exploring cell membrane water exchange in aquaporin-4-deficient ischemic mouse brain using diffusion-weighted MRI.

Authors:  Takuya Urushihata; Hiroyuki Takuwa; Manami Takahashi; Jeff Kershaw; Yasuhiko Tachibana; Nobuhiro Nitta; Sayaka Shibata; Masato Yasui; Makoto Higuchi; Takayuki Obata
Journal:  Eur Radiol Exp       Date:  2021-10-07

6.  DTI parameter optimisation for acquisition at 1.5T: SNR analysis and clinical application.

Authors:  M Laganà; M Rovaris; A Ceccarelli; C Venturelli; S Marini; G Baselli
Journal:  Comput Intell Neurosci       Date:  2010-01-05
  6 in total

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