Estimation of Covid-19 lungs damage based on computer tomography images analysis.

Q2 Pharmacology, Toxicology and Pharmaceutics
F1000Research Pub Date : 2025-07-25 eCollection Date: 2022-01-01 DOI:10.12688/f1000research.109020.3
Martin Schätz, Olga Rubešová, Jan Mareš, David Girsa, Alan Spark
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引用次数: 0

Abstract

Modern treatment is based on reproducible quantitative analysis of available data. The Covid-19 pandemic did accelerate development and research in several multidisciplinary areas. One of them is the use of software tools for faster and reproducible patient data evaluation. A CT scan can be invaluable for a search of details, but it is not always easy to see the big picture in 3D data. Even in the visual analysis of CT slice by slice can inter and intra variability makes a big difference. We present an ImageJ tool developed together with the radiology center of Faculty hospital Královské Vinohrady for CT evaluation of patients with COVID-19. The tool was developed to help estimate the percentage of lungs affected by the infection. The patients can be divided into five groups based on percentage score and proper treatment can be applied.

Abstract Image

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基于计算机断层图像分析的Covid-19肺损伤评估
现代治疗是基于对现有数据的可重复的定量分析。Covid-19大流行确实加速了几个多学科领域的开发和研究。其中之一是使用软件工具进行更快和可重复的患者数据评估。CT扫描对于搜索细节是无价的,但在3D数据中看到全局并不总是那么容易。即使在CT逐层的视觉分析中,内部和内部的变异性也会产生很大的差异。我们介绍了与学院医院放射学中心Královské Vinohrady共同开发的ImageJ工具,用于对COVID-19患者进行CT评估。开发该工具是为了帮助估计受感染肺部的百分比。将患者按百分率分为五组,采取相应的治疗措施。
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来源期刊
F1000Research
F1000Research Pharmacology, Toxicology and Pharmaceutics-Pharmacology, Toxicology and Pharmaceutics (all)
CiteScore
5.00
自引率
0.00%
发文量
1646
审稿时长
1 weeks
期刊介绍: F1000Research publishes articles and other research outputs reporting basic scientific, scholarly, translational and clinical research across the physical and life sciences, engineering, medicine, social sciences and humanities. F1000Research is a scholarly publication platform set up for the scientific, scholarly and medical research community; each article has at least one author who is a qualified researcher, scholar or clinician actively working in their speciality and who has made a key contribution to the article. Articles must be original (not duplications). All research is suitable irrespective of the perceived level of interest or novelty; we welcome confirmatory and negative results, as well as null studies. F1000Research publishes different type of research, including clinical trials, systematic reviews, software tools, method articles, and many others. Reviews and Opinion articles providing a balanced and comprehensive overview of the latest discoveries in a particular field, or presenting a personal perspective on recent developments, are also welcome. See the full list of article types we accept for more information.
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