The breast cancer will affect the skin surface temperature profile, whose thermophysical properties are very important for the diagnose of the disease. The temperature on the skin surface is analyzed by a 3-D layered breast model with variable metabolic heat generations and blood perfusion rates. The thermophysical properties of the breast are estimated by deep learning. The relationship between the temperature profiles and the thermophysical properties of the cancer is revealed. The research shows that infrared thermography with deep learning is a useful diagnostic tool for the breast cancer.
基金:
National Natural Science Foundation of China [12002181, 11921002, 11972205, 11672098, 11722218]
第一作者机构:[1]Hefei Univ Technol, Sch Civil Engn, Hefei 230009, Anhui, Peoples R China[2]Tsinghua Univ, Dept Engn Mech, Appl Mech Lab, Beijing, Peoples R China
通讯作者:
通讯机构:[1]Hefei Univ Technol, Sch Civil Engn, Hefei 230009, Anhui, Peoples R China[*1]School of Civil Engineering, Hefei University of Technology, Hefei, Anhui 230009 P.R. China.
推荐引用方式(GB/T 7714):
Chen Haolong,Wang Kaijie,Liu Zhanli,et al.Surface temperature analysis and thermophysical property estimation for breast cancer by deep learning[J].NUMERICAL HEAT TRANSFER PART A-APPLICATIONS.2022,82(8):411-427.doi:10.1080/10407782.2022.2079298.
APA:
Chen, Haolong,Wang, Kaijie,Liu, Zhanli&Zhou, Huanlin.(2022).Surface temperature analysis and thermophysical property estimation for breast cancer by deep learning.NUMERICAL HEAT TRANSFER PART A-APPLICATIONS,82,(8)
MLA:
Chen, Haolong,et al."Surface temperature analysis and thermophysical property estimation for breast cancer by deep learning".NUMERICAL HEAT TRANSFER PART A-APPLICATIONS 82..8(2022):411-427