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Studying the relative impact of ghosting and noise on the perceived quality of MR images

Abbey, Craig K., Liu, Hantao ORCID: https://orcid.org/0000-0003-4544-3481, Koonen, Jos, Fuderer, Miha, Heynderickx, Ingrid and Mello-Thoms, Claudia R. 2012. Studying the relative impact of ghosting and noise on the perceived quality of MR images. Presented at: SPIE Medical Imaging 2012, San Diego, California, 4-9 February 2012. Proceedings of SPIE. , vol.8318 Society of Photo-optical Instrumentation Engineers (SPIE), 10.1117/12.911019

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Abstract

In current magnetic resonance (MR) imaging systems, design choices are confronted with a trade-off between structured (i.e. artifacts) and unstructured noise. The impact of both types of noise on perceived image quality, however, is so far unknown, while this knowledge would be highly beneficial for further improvement of MR imaging systems. In this paper, we investigate how ghosting artifacts (i.e. structured noise) and random noise, applied at the same energy level in the distortion, affect the perceived quality of MR images. To this end, a perception experiment is conducted with human observers rating the quality of a set of images, distorted with various levels of ghosting and noise. To also understand the influence of professional expertise on the image quality assessment task, two groups of observers with different levels of medical imaging experience participated in the experiment: one group contained fifteen clinical scientists or application specialists, and the other group contained eighteen naïve observers. Experimental results indicate that experts and naïve observers differently assess the quality of MR images degraded with ghosting/noise. Naïve observers consistently rate images degraded with ghosting higher than images degraded with noise, independent of the energy level of the distortion, and of the image content. For experts, the relative impact of ghosting and noise on perceived quality tends to depend on the energy level of the distortion and on the image content, but overall the energy of the distortion is a promising metric to predict perceived image quality.

Item Type: Conference or Workshop Item (Paper)
Date Type: Published Online
Status: Published
Schools: Computer Science & Informatics
Publisher: Society of Photo-optical Instrumentation Engineers (SPIE)
ISSN: 0277-786X
Last Modified: 25 Oct 2022 13:07
URI: https://orca.cardiff.ac.uk/id/eprint/118919

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