RAD-IQMRI: A benchmark for MRI image quality assessment

Ma, Yueran, Lou, Jianxun, Tanguy, Jean-Yves, Corcoran, Padraig ORCID: https://orcid.org/0000-0001-9731-3385 and Liu, Hantao ORCID: https://orcid.org/0000-0003-4544-3481 2024. RAD-IQMRI: A benchmark for MRI image quality assessment. Neurocomputing 602 , 128292. 10.1016/j.neucom.2024.128292

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Abstract

Magnetic resonance imaging (MRI) is susceptible to visual artifacts that can degrade the perceptual image quality, potentially leading to inaccurate or inefficient diagnoses in clinical practice. It is critical to evaluate the perceptual image quality and build this technique into clinical solutions. In a previous study, an MRI database was created for image quality assessment (IQA), where various types of MRI artifacts with different degrees of degradation were simulated. Application specialists assessed the image quality; however, radiologists’ perception of MRI image quality remains unknown. To make IQA clinically relevant, in this paper we conduct a new subjective experiment where 13 radiologists rated the quality of images contained in the MRI database. Based on this subjective IQA benchmark named RAD-IQMRI, we evaluate the performance of state-of-the-art objective IQA models, providing insights into their application for MRI image quality assessment in clinical settings.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Additional Information:	License information from Publisher: LICENSE 1: URL: http://creativecommons.org/licenses/by/4.0/, Start Date: 2024-07-30
Publisher:	Elsevier
ISSN:	0925-2312
Date of First Compliant Deposit:	6 August 2024
Date of Acceptance:	28 July 2024
Last Modified:	06 Aug 2024 14:00
URI:	https://orca.cardiff.ac.uk/id/eprint/171214

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