International comparison of radiologists' assessment of the perceptual quality of medical ultrasound video

Leveque, Lucie, Zhang, Wei and Liu, Hantao ORCID: https://orcid.org/0000-0003-4544-3481 2019. International comparison of radiologists' assessment of the perceptual quality of medical ultrasound video. Presented at: 11th International Conference on Quality of Multimedia Experience (QoMEX 2019), Berlin, Germany, 5-7 June 2019. Proceedings of 2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX). IEEE, 10.1109/QoMEX.2019.8743180

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Abstract

Telemedicine can provide timely and high-quality clinical health care from a distance, improving access to and delivery of medical services in resource-poor settings. It can also save lives in situations of emergency. In many circumstances, the success of telemedicine practice heavily relies on the transmission of medical videos over large distances. However, video communication systems are prone to distortion in visual signals, affecting the task performance and thus putting patients at risk. It is critical to understand how practitioners perceive the quality of visual media and use such knowledge to improve clinical practice in telemedicine. In this paper, we investigate the hypothesis that visual quality perception varies between clinicians who work in different practice settings. To evaluate this hypothesis, we performed a subjective experiment where French and Chinese radiologists were asked to rate the quality of ultrasound videos compressed using different compression configurations. The results show that the way the perceived quality changes with the compression configuration is consistent among the both settings studied, however, French radiologists were more bothered by the compression artifacts. The findings can help inform future studies to develop tailored telemedicine systems for specific settings or individuals.

Item Type:	Conference or Workshop Item - published (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Schools > Computer Science & Informatics
Publisher:	IEEE
ISBN:	978-1-5386-8213-5
ISSN:	2372-7179
Date of First Compliant Deposit:	1 May 2019
Date of Acceptance:	26 February 2019
Last Modified:	14 May 2026 09:38
URI:	https://orca.cardiff.ac.uk/id/eprint/122004

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