CUQI: cardiac ultrasound video quality index

Razaak, Manzoor and Martini, Maria G (2016) CUQI: cardiac ultrasound video quality index. Journal of Medical Imaging, 3(1), 011011. ISSN (print) 2329-4302

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Abstract

Medical images and videos are now increasingly part of modern telecommunication applications, including telemedicinal applications, favored by advancements in video compression and communication technologies. Medical video quality evaluation is essential for modern applications since compression and transmission processes often compromise the video quality. Several state-of-the-art video quality metrics used for quality evaluation assess the perceptual quality of the video. For a medical video, assessing quality in terms of "diagnostic" value rather than "perceptual" quality is more important. We present a diagnostic-quality-oriented video quality metric for quality evaluation of cardiac ultrasound videos. Cardiac ultrasound videos are characterized by rapid repetitive cardiac motions and distinct structural information characteristics that are explored by the proposed metric. Cardiac ultrasound video quality index, the proposed metric, is a full reference metric and uses the motion and edge information of the cardiac ultrasound video to evaluate the video quality. The metric was evaluated for its performance in approximating the quality of cardiac ultrasound videos by testing its correlation with the subjective scores of medical experts. The results of our tests showed that the metric has high correlation with medical expert opinions and in several cases outperforms the state-of-the-art video quality metrics considered in our tests.

Item Type: Article
Additional Information: The research leading to these results have received funding from the European Union Seventh Framework Programme ([FP7/2007-2013]) under grant agreement N◦288502 (CONCERTO).
Research Area: Computer science and informatics
Other hospital based clinical subjects
Faculty, School or Research Centre: Faculty of Science, Engineering and Computing
Faculty of Science, Engineering and Computing > School of Computing and Information Systems
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Depositing User: Automatic Import Agent
Date Deposited: 14 Apr 2016 15:39
Last Modified: 13 Sep 2016 07:39
URI: http://eprints.kingston.ac.uk/id/eprint/34814

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