Predicting the thermophysical properties of skin tumor based on the surface temperature and deep learning

Chen, Haolong; Wang, Kaijie; Du, Z.; Liu, Weiming; Liu, Zhanli

doi:10.1016/j.ijheatmasstransfer.2021.121804

Cited by 20 publications

(6 citation statements)

References 45 publications

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“…Chen et al [76] estimated the depth, sizes, and thermal properties (thermal conductivity, heat generation, and blood perfusion) of skin tumors using a deep learning model and a 3D finite element, five-layer skin model. Skin surface temperatures during the thermal recovery phase were simulated by varying the features of a rectangular tumor lesion, and the obtained temperature data were used to train and test the performance of the neural network.…”

Section: Inverse Modelingmentioning

confidence: 99%

A Review of Techniques and Bio-Heat Transfer Models Supporting Infrared Thermal Imaging for Diagnosis of Malignancy

D’Alessandro,

Tavakolian,

Sfarra

2024

Applied Sciences

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The present review aims to analyze the application of infrared thermal imaging, aided by bio-heat models, as a tool for the diagnosis of skin and breast cancers. The state of the art of the related technical procedures, bio-heat transfer modeling, and thermogram post-processing methods is comprehensively reviewed. Once the thermal signatures of different malignant diseases are described, the updated thermographic techniques (steady-state and dynamic) used for cancer diagnosis are discussed in detail, along with the recommended best practices to ensure the most significant thermal contrast observable between the cancerous and healthy tissues. Regarding the dynamic techniques, particular emphasis is placed on innovative methods, such as lock-in thermography, thermal wave imaging, and rotational breast thermography. Forward and inverse modeling techniques for the bio-heat transfer in skin and breast tissues, supporting the thermographic examination and providing accurate data for training artificial intelligence (AI) algorithms, are reported with a special focus on real breast geometry-based 3D models. In terms of inverse techniques, different data processing algorithms to retrieve thermophysical parameters and growth features of tumor lesions are mentioned. Post-processing of infrared images is also described, citing both conventional processing procedures and applications of AI algorithms for tumor detection.

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Section: Inverse Modelingmentioning

confidence: 99%

A Review of Techniques and Bio-Heat Transfer Models Supporting Infrared Thermal Imaging for Diagnosis of Malignancy

D’Alessandro,

Tavakolian,

Sfarra

2024

Applied Sciences

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“…Table 1. Geometric and thermal properties of media [11]. It should be noted that the non-linear terms in Equation ( 4) have been discretized using the temperature from the previous time level.…”

Section: Mathematical Model and Numerical Techniquementioning

confidence: 99%

“…As a result, it is important to define and describe the condition of melanoma. Chen et al [11] have identified the relationship between the thermal characteristics of a tumor and the surface temperature of the skin using dynamic thermography and a deep learning model. The used technique for the inverse bio-thermal conduction problem determines the overall thermal properties of the tumor.…”

Section: Introductionmentioning

confidence: 99%

Mathematical Simulation of Bio-Heat Transfer in Tissues Having Five Layers in the Presence of a Tumor Zone

Akulova,

Sheremet

2024

Mathematics

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A presence of tumor zones within biological tissues can be defined during the analysis of the skin surface temperature. This research is devoted to mathematical simulation of the time-dependent bio-heat transfer in tissues under a tumor influence. The one-dimensional partial differential equation of the Pennes model has been used for description of bio-heat transfer within the biological tissue with five layers, namely, epidermis, papillary dermis, reticular dermis, subcutaneous adipose tissue, and a muscle layer. The formulated boundary-value problem has been solved using the developed in-house computational code based on the finite difference schemes. The developed numerical algorithm has been verified using analytical and numerical solutions of other authors for the simpler test problem. As a result of this study, the temperature distributions have been obtained for the tissue in the presence of tumor zones in different layers of the skin. The influence of five layers of skin on the temperature distribution has been investigated, and the dependence for the skin surface temperature on the tumor zone location has been obtained. The obtained outcomes illustrate the effectiveness of this technique of cancer diagnosis and identify the optimal parameters for its application. Thus, this work represents an important step in the development of cancer diagnosis methods using thermography. The results obtained can be used to improve the accuracy of diagnosis and develop new treatment methods.

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“…These improvements, combined with the increasing computational power and the advent of artificial intelligence (AI) algorithms for simulation, are envisioned to become a major part of the preclinical optimization/ validation process of hyperthermia therapies and of the research to predict their effect on healthy tissues. 239,256,257 4 Advances in preclinical screening of hyperthermic nanomedicines in 3D tumor models…”

Section: Heat Response and Transfer Mechanisms: Probing Dimensional I...mentioning

confidence: 99%

Advances in screening hyperthermic nanomedicines in 3D tumor models

Soeiro,

Sousa,

Monteiro

et al. 2024

Nanoscale Horiz.

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Predicting the thermophysical properties of skin tumor based on the surface temperature and deep learning

Cited by 20 publications

References 45 publications

A Review of Techniques and Bio-Heat Transfer Models Supporting Infrared Thermal Imaging for Diagnosis of Malignancy

A Review of Techniques and Bio-Heat Transfer Models Supporting Infrared Thermal Imaging for Diagnosis of Malignancy

Mathematical Simulation of Bio-Heat Transfer in Tissues Having Five Layers in the Presence of a Tumor Zone

Advances in screening hyperthermic nanomedicines in 3D tumor models

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