TY - GEN
T1 - Automated features analysis of patients with spinal diseases using medical thermal images
AU - Vassilenko, Valentina
AU - Poplavska, Anna
AU - Pavlov, Sergiy
AU - Kolisnyk, Petro
AU - Poplavskyi, Oleksandr
AU - Kolisnyk, Sergiy
AU - Vitrova, Yuliia
AU - Wójcik, Waldemar
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Abnormal temperature regions
KW - Automated segmentation
KW - Infrared thermography
KW - Medical thermal images
UR - http://www.scopus.com/inward/record.url?scp=85088017016&partnerID=8YFLogxK
U2 - 10.1117/12.2569780
DO - 10.1117/12.2569780
M3 - Conference contribution
AN - SCOPUS:85088017016
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Optical Fibers and Their Applications 2020
A2 - Romaniuk, Ryszard S.
A2 - Dorosz, Jan
PB - SPIE-International Society for Optical Engineering
T2 - Optical Fibers and Their Applications 2020
Y2 - 27 January 2020 through 31 January 2020
ER -