V. Vassilenko, Anna A. Poplavska, S. Pavlov, P. Kolisnyk, Oleksandr A. Poplavskyi, Sergiy Kolisnyk, Yuliia Vitrova, W. Wójcik
{"title":"Automated features analysis of patients with spinal diseases using medical thermal images","authors":"V. Vassilenko, Anna A. Poplavska, S. Pavlov, P. Kolisnyk, Oleksandr A. Poplavskyi, Sergiy Kolisnyk, Yuliia Vitrova, W. Wójcik","doi":"10.1117/12.2569780","DOIUrl":null,"url":null,"abstract":"Nowadays, the medical infrared thermal imaging (MITI) techniques can provide good quality images in real-time for monitoring and pre-clinical diagnostic of the diseases caused by inflammatory processes by showing the thermal abnormalities present in the body. MITI allows specify of the functional changes in the normal temperature distribution on the surface of the body, as well as enables refinement the localization of functional changes, the activity of the process, its prevalence and the nature of the changes – inflammation, stagnation, malignancy, etc. Due to its non-contact, non-invasive and non-destructive way of using, this technology has a distinct advantage among other diagnostic methods. Therefore, the main objectives of this research work were automated steps of feature extraction and analysis MTIs, i.e. to develop novel algorithm for quantitative interpretation of thermal images database, to improve the experimental protocol of obtaining thermal images and to perform an extensive field measurement in the selected cohort of patients, in our case, with spinal diseases, in order to provide an immediate high-quality solutions in real time clinical validation of the proposed method.","PeriodicalId":299297,"journal":{"name":"Optical Fibers and Their Applications","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optical Fibers and Their Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2569780","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Nowadays, the medical infrared thermal imaging (MITI) techniques can provide good quality images in real-time for monitoring and pre-clinical diagnostic of the diseases caused by inflammatory processes by showing the thermal abnormalities present in the body. MITI allows specify of the functional changes in the normal temperature distribution on the surface of the body, as well as enables refinement the localization of functional changes, the activity of the process, its prevalence and the nature of the changes – inflammation, stagnation, malignancy, etc. Due to its non-contact, non-invasive and non-destructive way of using, this technology has a distinct advantage among other diagnostic methods. Therefore, the main objectives of this research work were automated steps of feature extraction and analysis MTIs, i.e. to develop novel algorithm for quantitative interpretation of thermal images database, to improve the experimental protocol of obtaining thermal images and to perform an extensive field measurement in the selected cohort of patients, in our case, with spinal diseases, in order to provide an immediate high-quality solutions in real time clinical validation of the proposed method.