Biomedical Applications of Infrared Thermal Imaging: Current State of Machine Learning Classification

Biomedical Applications of Infrared Thermal Imaging: Current State of Machine Learning Classification

Infrared thermal (IRT) imaging is a modality that allows non-invasive and non-ionizing monitoring of skin surface temperature distribution, providing underlining physiological information on peripheral blood flow, autonomic nervous system, vasoconstriction/vasodilatation, inflammation, transpiration...

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Bibliographic Details
Main Authors: Ricardo Vardasca, Carolina Magalhaes, Joaquim Mendes
Format: Article
Language:English
Published: MDPI AG 2019-10-01
Series:Proceedings
Subjects:
biomedical applications
classification
infrared thermal imaging
machine learning
Online Access:https://www.mdpi.com/2504-3900/27/1/46
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spelling doaj-0fdbc86d95104040b4a4063bee5d85d42020-11-25T02:36:22ZengMDPI AGProceedings2504-39002019-10-012714610.3390/proceedings2019027046proceedings2019027046Biomedical Applications of Infrared Thermal Imaging: Current State of Machine Learning ClassificationRicardo Vardasca0Carolina Magalhaes1Joaquim Mendes2INEGI-LAETA, Faculdade de Engenharia, Universidade do Porto, 4200-465 Porto, PortugalINEGI-LAETA, Faculdade de Engenharia, Universidade do Porto, 4200-465 Porto, PortugalINEGI-LAETA, Faculdade de Engenharia, Universidade do Porto, 4200-465 Porto, PortugalInfrared thermal (IRT) imaging is a modality that allows non-invasive and non-ionizing monitoring of skin surface temperature distribution, providing underlining physiological information on peripheral blood flow, autonomic nervous system, vasoconstriction/vasodilatation, inflammation, transpiration or other processes that can contribute to skin temperature. This imaging method has been used in biomedical applications since 1956 and has proved its usefulness for vascular, neurological and musculoskeletal pathological situations. This research aims to identify and appraise the recent biomedical applications which had used intelligent analysis methods such as machine learning processes to classify and perform decision making towards improving the existing medical care, a literature review is presented and their operation in the biomedical applications of infrared thermal imaging.https://www.mdpi.com/2504-3900/27/1/46biomedical applicationsclassificationinfrared thermal imagingmachine learning
collection DOAJ
language English
format Article
sources DOAJ
author Ricardo Vardasca
Carolina Magalhaes
Joaquim Mendes
spellingShingle Ricardo Vardasca
Carolina Magalhaes
Joaquim Mendes
Biomedical Applications of Infrared Thermal Imaging: Current State of Machine Learning Classification
Proceedings
biomedical applications
classification
infrared thermal imaging
machine learning
author_facet Ricardo Vardasca
Carolina Magalhaes
Joaquim Mendes
author_sort Ricardo Vardasca
title Biomedical Applications of Infrared Thermal Imaging: Current State of Machine Learning Classification
title_short Biomedical Applications of Infrared Thermal Imaging: Current State of Machine Learning Classification
title_full Biomedical Applications of Infrared Thermal Imaging: Current State of Machine Learning Classification
title_fullStr Biomedical Applications of Infrared Thermal Imaging: Current State of Machine Learning Classification
title_full_unstemmed Biomedical Applications of Infrared Thermal Imaging: Current State of Machine Learning Classification
title_sort biomedical applications of infrared thermal imaging: current state of machine learning classification
publisher MDPI AG
series Proceedings
issn 2504-3900
publishDate 2019-10-01
description Infrared thermal (IRT) imaging is a modality that allows non-invasive and non-ionizing monitoring of skin surface temperature distribution, providing underlining physiological information on peripheral blood flow, autonomic nervous system, vasoconstriction/vasodilatation, inflammation, transpiration or other processes that can contribute to skin temperature. This imaging method has been used in biomedical applications since 1956 and has proved its usefulness for vascular, neurological and musculoskeletal pathological situations. This research aims to identify and appraise the recent biomedical applications which had used intelligent analysis methods such as machine learning processes to classify and perform decision making towards improving the existing medical care, a literature review is presented and their operation in the biomedical applications of infrared thermal imaging.
topic biomedical applications
classification
infrared thermal imaging
machine learning
url https://www.mdpi.com/2504-3900/27/1/46
work_keys_str_mv AT ricardovardasca biomedicalapplicationsofinfraredthermalimagingcurrentstateofmachinelearningclassification
AT carolinamagalhaes biomedicalapplicationsofinfraredthermalimagingcurrentstateofmachinelearningclassification
AT joaquimmendes biomedicalapplicationsofinfraredthermalimagingcurrentstateofmachinelearningclassification
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