HORVAT, Ivan Dominik ;ILJAŽ, Jurij . Numerical solving of dynamic thermography inverse problem for skin cancer diagnosis based on non-Fourier bioheat model. Articles in Press, [S.l.], v. 0, n.0, p. , july 2025. ISSN 0039-2480. Available at: <https://www.sv-jme.eu/sl/article/numerical-solving-of-dynamic-thermography-inverse-problem-for-skin-cancer-diagnosis-based-on-non-fourier-bioheat-model/>. Date accessed: 15 sep. 2025. doi:http://dx.doi.org/.
Horvat, I., & Iljaž, J. (0). Numerical solving of dynamic thermography inverse problem for skin cancer diagnosis based on non-Fourier bioheat model. Articles in Press, 0(0), . doi:http://dx.doi.org/
@article{.,
author = {Ivan Dominik Horvat and Jurij Iljaž},
title = {Numerical solving of dynamic thermography inverse problem for skin cancer diagnosis based on non-Fourier bioheat model},
journal = {Articles in Press},
volume = {0},
number = {0},
year = {0},
keywords = {numerical modeling; dynamic thermography; inverse problem; non-Fourier bioheat transfer; dual-phase-lag model; boundary element method; Levenberg-Marquardt optimization; },
abstract = {This paper presents numerical solving of the inverse bioheat problem using non-Fourier skin cancer model to enhance diagnostics through dynamic thermography to estimate four tumor parameters; diameter, thickness, blood perfusion rate and thermal relaxation time. A 3D multilayer biological tissue model is developed, incorporating distinct thermophysical properties and embedded Clark II and Clark IV melanoma tumors. The non-Fourier dual-phase-lag bioheat model is used to describe heat transfer in the heterogeneous, blood-perfused structure of human skin. Dynamic thermography is simulated through a cold air jet cooling phase followed by metabolic and perfusion-driven rewarming using the boundary element method, while inverse bioheat problem has been solved using the hybrid Levenberg-Marquardt optimization method. Measurement data for solving inverse problem has been generated numerically with known exact tumor parameters and added noise, in order to evaluate the accuracy and sensitivity of the solution. Inverse problem solution has also been tested for two different thermal responses; absolute temperature and temperature difference response. All important tumor parameters were successfully retrieved especially the diameter and relaxation time, even for the high level of noise, demonstrating the robustness of the method and a promising way for early diagnosis. The findings contribute to improving bioheat modeling in biological tissues, solving inverse bioheat problems and advancing dynamic thermography as a non-invasive tool for early skin cancer diagnosis.},
issn = {0039-2480}, pages = {}, doi = {},
url = {https://www.sv-jme.eu/sl/article/numerical-solving-of-dynamic-thermography-inverse-problem-for-skin-cancer-diagnosis-based-on-non-fourier-bioheat-model/}
}
Horvat, I.,Iljaž, J. 0 July 0. Numerical solving of dynamic thermography inverse problem for skin cancer diagnosis based on non-Fourier bioheat model. Articles in Press. [Online] 0:0
%A Horvat, Ivan Dominik %A Iljaž, Jurij %D 0 %T Numerical solving of dynamic thermography inverse problem for skin cancer diagnosis based on non-Fourier bioheat model %B 0 %9 numerical modeling; dynamic thermography; inverse problem; non-Fourier bioheat transfer; dual-phase-lag model; boundary element method; Levenberg-Marquardt optimization; %! Numerical solving of dynamic thermography inverse problem for skin cancer diagnosis based on non-Fourier bioheat model %K numerical modeling; dynamic thermography; inverse problem; non-Fourier bioheat transfer; dual-phase-lag model; boundary element method; Levenberg-Marquardt optimization; %X This paper presents numerical solving of the inverse bioheat problem using non-Fourier skin cancer model to enhance diagnostics through dynamic thermography to estimate four tumor parameters; diameter, thickness, blood perfusion rate and thermal relaxation time. A 3D multilayer biological tissue model is developed, incorporating distinct thermophysical properties and embedded Clark II and Clark IV melanoma tumors. The non-Fourier dual-phase-lag bioheat model is used to describe heat transfer in the heterogeneous, blood-perfused structure of human skin. Dynamic thermography is simulated through a cold air jet cooling phase followed by metabolic and perfusion-driven rewarming using the boundary element method, while inverse bioheat problem has been solved using the hybrid Levenberg-Marquardt optimization method. Measurement data for solving inverse problem has been generated numerically with known exact tumor parameters and added noise, in order to evaluate the accuracy and sensitivity of the solution. Inverse problem solution has also been tested for two different thermal responses; absolute temperature and temperature difference response. All important tumor parameters were successfully retrieved especially the diameter and relaxation time, even for the high level of noise, demonstrating the robustness of the method and a promising way for early diagnosis. The findings contribute to improving bioheat modeling in biological tissues, solving inverse bioheat problems and advancing dynamic thermography as a non-invasive tool for early skin cancer diagnosis. %U https://www.sv-jme.eu/sl/article/numerical-solving-of-dynamic-thermography-inverse-problem-for-skin-cancer-diagnosis-based-on-non-fourier-bioheat-model/ %0 Journal Article %R %& %P 1 %J Articles in Press %V 0 %N 0 %@ 0039-2480 %8 2025-07-17 %7 2025-07-17
Horvat, Ivan Dominik, & Jurij Iljaž. "Numerical solving of dynamic thermography inverse problem for skin cancer diagnosis based on non-Fourier bioheat model." Articles in Press [Online], 0.0 (0): . Web. 15 Sep. 2025
TY - JOUR AU - Horvat, Ivan Dominik AU - Iljaž, Jurij PY - 0 TI - Numerical solving of dynamic thermography inverse problem for skin cancer diagnosis based on non-Fourier bioheat model JF - Articles in Press DO - KW - numerical modeling; dynamic thermography; inverse problem; non-Fourier bioheat transfer; dual-phase-lag model; boundary element method; Levenberg-Marquardt optimization; N2 - This paper presents numerical solving of the inverse bioheat problem using non-Fourier skin cancer model to enhance diagnostics through dynamic thermography to estimate four tumor parameters; diameter, thickness, blood perfusion rate and thermal relaxation time. A 3D multilayer biological tissue model is developed, incorporating distinct thermophysical properties and embedded Clark II and Clark IV melanoma tumors. The non-Fourier dual-phase-lag bioheat model is used to describe heat transfer in the heterogeneous, blood-perfused structure of human skin. Dynamic thermography is simulated through a cold air jet cooling phase followed by metabolic and perfusion-driven rewarming using the boundary element method, while inverse bioheat problem has been solved using the hybrid Levenberg-Marquardt optimization method. Measurement data for solving inverse problem has been generated numerically with known exact tumor parameters and added noise, in order to evaluate the accuracy and sensitivity of the solution. Inverse problem solution has also been tested for two different thermal responses; absolute temperature and temperature difference response. All important tumor parameters were successfully retrieved especially the diameter and relaxation time, even for the high level of noise, demonstrating the robustness of the method and a promising way for early diagnosis. The findings contribute to improving bioheat modeling in biological tissues, solving inverse bioheat problems and advancing dynamic thermography as a non-invasive tool for early skin cancer diagnosis. UR - https://www.sv-jme.eu/sl/article/numerical-solving-of-dynamic-thermography-inverse-problem-for-skin-cancer-diagnosis-based-on-non-fourier-bioheat-model/
@article{{}{.},
author = {Horvat, I., Iljaž, J.},
title = {Numerical solving of dynamic thermography inverse problem for skin cancer diagnosis based on non-Fourier bioheat model},
journal = {Articles in Press},
volume = {0},
number = {0},
year = {0},
doi = {},
url = {https://www.sv-jme.eu/sl/article/numerical-solving-of-dynamic-thermography-inverse-problem-for-skin-cancer-diagnosis-based-on-non-fourier-bioheat-model/}
}
TY - JOUR AU - Horvat, Ivan Dominik AU - Iljaž, Jurij PY - 2025/07/17 TI - Numerical solving of dynamic thermography inverse problem for skin cancer diagnosis based on non-Fourier bioheat model JF - Articles in Press; Vol 0, No 0 (0): Articles in Press DO - KW - numerical modeling, dynamic thermography, inverse problem, non-Fourier bioheat transfer, dual-phase-lag model, boundary element method, Levenberg-Marquardt optimization, N2 - This paper presents numerical solving of the inverse bioheat problem using non-Fourier skin cancer model to enhance diagnostics through dynamic thermography to estimate four tumor parameters; diameter, thickness, blood perfusion rate and thermal relaxation time. A 3D multilayer biological tissue model is developed, incorporating distinct thermophysical properties and embedded Clark II and Clark IV melanoma tumors. The non-Fourier dual-phase-lag bioheat model is used to describe heat transfer in the heterogeneous, blood-perfused structure of human skin. Dynamic thermography is simulated through a cold air jet cooling phase followed by metabolic and perfusion-driven rewarming using the boundary element method, while inverse bioheat problem has been solved using the hybrid Levenberg-Marquardt optimization method. Measurement data for solving inverse problem has been generated numerically with known exact tumor parameters and added noise, in order to evaluate the accuracy and sensitivity of the solution. Inverse problem solution has also been tested for two different thermal responses; absolute temperature and temperature difference response. All important tumor parameters were successfully retrieved especially the diameter and relaxation time, even for the high level of noise, demonstrating the robustness of the method and a promising way for early diagnosis. The findings contribute to improving bioheat modeling in biological tissues, solving inverse bioheat problems and advancing dynamic thermography as a non-invasive tool for early skin cancer diagnosis. UR - https://www.sv-jme.eu/sl/article/numerical-solving-of-dynamic-thermography-inverse-problem-for-skin-cancer-diagnosis-based-on-non-fourier-bioheat-model/
Horvat, Ivan Dominik, AND Iljaž, Jurij. "Numerical solving of dynamic thermography inverse problem for skin cancer diagnosis based on non-Fourier bioheat model" Articles in Press [Online], Volume 0 Number 0 (17 July 2025)
Articles in Press
This paper presents numerical solving of the inverse bioheat problem using non-Fourier skin cancer model to enhance diagnostics through dynamic thermography to estimate four tumor parameters; diameter, thickness, blood perfusion rate and thermal relaxation time. A 3D multilayer biological tissue model is developed, incorporating distinct thermophysical properties and embedded Clark II and Clark IV melanoma tumors. The non-Fourier dual-phase-lag bioheat model is used to describe heat transfer in the heterogeneous, blood-perfused structure of human skin. Dynamic thermography is simulated through a cold air jet cooling phase followed by metabolic and perfusion-driven rewarming using the boundary element method, while inverse bioheat problem has been solved using the hybrid Levenberg-Marquardt optimization method. Measurement data for solving inverse problem has been generated numerically with known exact tumor parameters and added noise, in order to evaluate the accuracy and sensitivity of the solution. Inverse problem solution has also been tested for two different thermal responses; absolute temperature and temperature difference response. All important tumor parameters were successfully retrieved especially the diameter and relaxation time, even for the high level of noise, demonstrating the robustness of the method and a promising way for early diagnosis. The findings contribute to improving bioheat modeling in biological tissues, solving inverse bioheat problems and advancing dynamic thermography as a non-invasive tool for early skin cancer diagnosis.