A novel algorithm for comprehensive quality assessment of clinical magnetic resonance images based on natural scene statistics in spatial domain

Yoichiro Ikushima, Shogo Tokurei, Hiroyuki Tarewaki, Junji Morishita, Hidetake Yabuuchi

Research output: Contribution to journalArticlepeer-review

Abstract

Background: A magnetic resonance imaging (MRI)-specific objective image quality assessment (IQA) algorithm, the quality evaluation using multidirectional filters for MRI (QEMDIM), was previously reported. QEMDIM requires a set of reference images to calculate the quality score (SQ) for an assessed image. SQ may be affected by the quality of the reference set owing to the calculation procedure. Purpose: To propose a modified version of the IQA algorithm and compare the IQA performance of the original and modified algorithms. Assessment: Brain axial T1- and T2-weighted spin-echo images of varying quality levels (noise and blurring) were acquired from seven healthy men. Subjective IQA (paired comparisons) was conducted on the images, and subjective quality scores were obtained. With reference sets of various quality levels, QEMDIM and modified IQA were applied to the same images that underwent the subjective IQA. The correlation of each SQ and modified score (Smod) with the subjective scores was evaluated for content-related subsets of assessed images and for each reference set. The effect of the reference-set quality on the distribution of the correlation coefficients (CCs) was statistically evaluated for SQ and Smod using a one-way analysis of variance test with a significance level of 0.05. We also evaluated the variation in Smod for images with almost the same qualities using the standard deviation (SD). Results: The CCs of SQ varied significantly with the quality of the reference set, whereas that of Smod did not. The SD of Smod for almost-same-quality images was less than that corresponding to the confidence interval of the subjective scores. Conclusion: Our modified algorithm was superior to QEMDIM in terms of IQA performance in clinical practice, especially in terms of accuracy, robustness, and reproducibility.

Original languageEnglish
Pages (from-to)203-211
Number of pages9
JournalMagnetic Resonance Imaging
Volume92
DOIs
Publication statusPublished - Oct 2022

All Science Journal Classification (ASJC) codes

  • Biophysics
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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