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Proceedings Paper

The study of surgical image quality evaluation system by subjective quality factor method
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Paper Abstract

GreenLightTM procedure is an effective and economical way of treatment of benign prostate hyperplasia (BPH); there are almost a million of patients treated with GreenLightTM worldwide. During the surgical procedure, the surgeon or physician will rely on the monitoring video system to survey and confirm the surgical progress. There are a few obstructions that could greatly affect the image quality of the monitoring video, like laser glare by the tissue and body fluid, air bubbles and debris generated by tissue evaporation, and bleeding, just to name a few. In order to improve the physician’s visual experience of a laser surgical procedure, the system performance parameter related to image quality needs to be well defined. However, since image quality is the integrated set of perceptions of the overall degree of excellence of an image, or in other words, image quality is the perceptually weighted combination of significant attributes (contrast, graininess …) of an image when considered in its marketplace or application, there is no standard definition on overall image or video quality especially for the no-reference case (without a standard chart as reference). In this study, Subjective Quality Factor (SQF) and acutance are used for no-reference image quality evaluation. Basic image quality parameters, like sharpness, color accuracy, size of obstruction and transmission of obstruction, are used as subparameter to define the rating scale for image quality evaluation or comparison. Sample image groups were evaluated by human observers according to the rating scale. Surveys of physician groups were also conducted with lab generated sample videos. The study shows that human subjective perception is a trustworthy way of image quality evaluation. More systematic investigation on the relationship between video quality and image quality of each frame will be conducted as a future study.

Paper Details

Date Published: 24 March 2016
PDF: 8 pages
Proc. SPIE 9787, Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, 97871B (24 March 2016); doi: 10.1117/12.2214920
Show Author Affiliations
Jian J. Zhang, Boston Scientific Corp. (United States)
Jason R. Xuan, Boston Scientific Corp. (United States)
Xirong Yang, Boston Scientific Corp. (United States)
Honggang Yu, Boston Scientific Corp. (United States)
Edouard Koullick, Boston Scientific Corp. (United States)


Published in SPIE Proceedings Vol. 9787:
Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment
Craig K. Abbey; Matthew A. Kupinski, Editor(s)

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