Comparative study of the methodologies used for subjective medical image quality assessment

质量(理念) 感知 多样性(控制论) 医疗实践 任务(项目管理) 临床实习 医疗保健 情感(语言学) 医学影像学 计算机科学 医学教育 心理学 医学 数据科学 人工智能 护理部 经济 管理 神经科学 沟通 哲学 认识论 经济增长
作者
Lucie Lévêque,Meriem Outtas,Hantao Liu,Lu Zhang
出处
期刊:Physics in Medicine and Biology [IOP Publishing]
卷期号:66 (15): 15TR02-15TR02 被引量:15
标识
DOI:10.1088/1361-6560/ac1157
摘要

Healthcare professionals have been increasingly viewing medical images and videos in their routine clinical practice, and this in a wide variety of environments. Both the perception and interpretation of medical visual information, across all branches of practice or medical specialties (e.g. diagnostic, therapeutic, or surgical medicine), career stages, and practice settings (e.g. emergency care), appear to be critical for patient care. However, medical images and videos are not self-explanatory and, therefore, need to be interpreted by humans, i.e. medical experts. In addition, various types of degradations and artifacts may appear during image acquisition or processing, and consequently affect medical imaging data. Such distortions tend to impact viewers' quality of experience, as well as their clinical practice. It is accordingly essential to better understand how medical experts perceive the quality of visual content. Thankfully, progress has been made in the recent literature towards such understanding. In this article, we present an up-to-date state-of the-art of relatively recent (i.e. not older than ten years old) existing studies on the subjective quality assessment of medical images and videos, as well as research works using task-based approaches. Furthermore, we discuss the merits and drawbacks of the methodologies used, and we provide recommendations about experimental designs and statistical processes to evaluate the perception of medical images and videos for future studies, which could then be used to optimise the visual experience of image readers in real clinical practice. Finally, we tackle the issue of the lack of available annotated medical image and video quality databases, which appear to be indispensable for the development of new dedicated objective metrics.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Dsweet发布了新的文献求助10
刚刚
1秒前
Weining发布了新的文献求助10
1秒前
1秒前
高贵的海安完成签到,获得积分10
1秒前
长期不想取网名完成签到,获得积分10
2秒前
感动满天发布了新的文献求助10
3秒前
刘YF发布了新的文献求助10
3秒前
3秒前
yye发布了新的文献求助10
4秒前
蒙先生发布了新的文献求助30
4秒前
田様应助zyn采纳,获得10
4秒前
L一年发布了新的文献求助10
5秒前
5秒前
5秒前
李李原上完成签到,获得积分20
7秒前
顾文杰完成签到 ,获得积分10
8秒前
大有阳光应助旺旺采纳,获得10
8秒前
好困应助Dsweet采纳,获得10
9秒前
共享精神应助Dsweet采纳,获得10
9秒前
围城发布了新的文献求助30
9秒前
李李原上发布了新的文献求助10
10秒前
陈军应助星辰采纳,获得20
10秒前
12秒前
犹豫的棒棒糖完成签到,获得积分10
12秒前
12秒前
甜甜玫瑰应助温婉的含芙采纳,获得10
13秒前
iNk应助轩贝采纳,获得20
13秒前
13秒前
吃大肉完成签到,获得积分10
13秒前
cnsnfsafmiima完成签到,获得积分10
14秒前
15秒前
15秒前
lilililili发布了新的文献求助10
15秒前
16秒前
寻雪完成签到,获得积分10
16秒前
情怀应助TTT采纳,获得10
16秒前
执着半烟完成签到,获得积分10
16秒前
彩色剑完成签到,获得积分10
16秒前
swq发布了新的文献求助10
16秒前
高分求助中
Evolution 10000
Sustainability in Tides Chemistry 2800
юрские динозавры восточного забайкалья 800
English Wealden Fossils 700
A new species of Coccus (Homoptera: Coccoidea) from Malawi 500
A new species of Velataspis (Hemiptera Coccoidea Diaspididae) from tea in Assam 500
Diagnostic immunohistochemistry : theranostic and genomic applications 6th Edition 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3156221
求助须知:如何正确求助?哪些是违规求助? 2807720
关于积分的说明 7874164
捐赠科研通 2465918
什么是DOI,文献DOI怎么找? 1312504
科研通“疑难数据库(出版商)”最低求助积分说明 630154
版权声明 601912