2018
Lévêque, Lucie; Liu, Hantao; Baraković, Sabina; Husić, Jasmina Baraković; Martini, Maria; Outtas, Meriem; Zhang, Lu; Kumcu, Asli; Platisa, Ljiljana; Rodrigues, Rafael; others,
On the subjective assessment of the perceived quality of medical images and videos Proceedings Article
In: 2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX), pp. 1–6, IEEE 2018.
Abstract | Links | BibTeX | Tags: image quality assessment, medical image quality, MOS, subjective experiment, video quality assessment
@inproceedings{Lévêque2018b,
title = {On the subjective assessment of the perceived quality of medical images and videos},
author = {Lucie Lévêque and Hantao Liu and Sabina Baraković and Jasmina Baraković Husić and Maria Martini and Meriem Outtas and Lu Zhang and Asli Kumcu and Ljiljana Platisa and Rafael Rodrigues and others},
url = {https://ieeexplore.ieee.org/document/8463297?part=1},
doi = {10.1109/QoMEX.2018.8463297},
year = {2018},
date = {2018-01-01},
booktitle = {2018 Tenth International Conference on Quality of Multimedia Experience (QoMEX)},
pages = {1--6},
organization = {IEEE},
abstract = {Medical professionals are viewing an increasing number of images and videos in their clinical routine. However, various types of distortions can affect medical imaging data, and therefore impact the viewers' experienced quality and their clinical practice. Thus it is necessary to quantify this impact and understand how the viewers, i.e., medical experts, perceive the quality of (distorted) images and videos. In this paper, we present an up-to-date review of the methodologies used in the literature for the subjective quality assessment of medical images and videos and discuss their merits and drawbacks depending on the use case.},
keywords = {image quality assessment, medical image quality, MOS, subjective experiment, video quality assessment},
pubstate = {published},
tppubtype = {inproceedings}
}
Medical professionals are viewing an increasing number of images and videos in their clinical routine. However, various types of distortions can affect medical imaging data, and therefore impact the viewers' experienced quality and their clinical practice. Thus it is necessary to quantify this impact and understand how the viewers, i.e., medical experts, perceive the quality of (distorted) images and videos. In this paper, we present an up-to-date review of the methodologies used in the literature for the subjective quality assessment of medical images and videos and discuss their merits and drawbacks depending on the use case.