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Defect Identification in Thermographic Nondestructive Testing under Cyclic Heating Using SVD Thermo-Component Analysis 利用 SVD 热成分分析鉴定循环加热条件下热成像无损检测中的缺陷
Pub Date : 2023-12-12 DOI: 10.3390/engproc2023051042
Shoma Oiso, D. Shiozawa, Yuki Ogawa, T. Sakagami
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引用次数: 0
Monitoring Moisture Diffusion after Contact Sponge Application 监测接触式海绵应用后的湿气扩散情况
Pub Date : 2023-12-12 DOI: 10.3390/engproc2023051041
P. Bison, G. Cadelano, G. Ferrarini, M. Girotto, E. Guolo, Fabio Peron, M. Volinia
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引用次数: 0
Train Pulses with a Random Spatial Distribution to Measure In-Plane Thermal Diffusivity 用随机空间分布列车脉冲测量平面内热扩散率
Pub Date : 2023-11-30 DOI: 10.3390/engproc2023051039
P. Bison, G. Ferrarini, Christ Glorieux, Shuji Kamegaki, Junko Morikawa, Stefano Rossi, M. Ryu
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引用次数: 0
Diagnostic Biomarker for Breast Cancer Applying Rayleigh Low-Rank Embedding Thermography 应用瑞利低方根嵌入式热成像技术的乳腺癌诊断生物标志物
Pub Date : 2023-11-29 DOI: 10.3390/engproc2023051038
B. Yousefi, Xavier Maldague, F. Hassanipour
: Thermography has found extensive application as a supplementary diagnostic tool in breast cancer diagnosis, notably complementing the clinical breast exam (CBE). Within dynamic thermography, matrix factorization methods have demonstrated their utility in accentuating thermal heterogeneities by generating thermal basis vectors. A significant challenge in such approaches is to identify the leading thermal basis vector that effectively captures predominant thermal patterns. Embedding methods are used to fuse multiple projected basis vectors onto a single basis for the extraction of the thermal features, known as thermomics . In this study, we introduce Rayleigh embedding to project thermal basis vectors obtained from factorization techniques into a lower-dimensional space, highlighting thermal patterns. This enhances the reliability of the thermal system, thereby assisting in CBE. The best results of the embedding method combining clinical information and demographics yield 82.9% (66.7%, 86.7%) using a random forest. The results demonstrated promising preliminary outcomes, leading to the early detection of breast abnormalities, and can serve as a non-invasive tool to aid CBE.
:热成像技术作为一种辅助诊断工具,在乳腺癌诊断中得到了广泛应用,特别是对临床乳房检查(CBE)起到了补充作用。在动态热成像技术中,矩阵因式分解方法通过生成热基矢量来突出热异质性,显示了其实用性。这类方法面临的一个重大挑战是如何确定能有效捕捉主要热模式的主要热基向量。嵌入方法用于将多个投影基向量融合到单个基上,以提取热特征,即所谓的热组学。在本研究中,我们引入了瑞利嵌入法,将因式分解技术获得的热基向量投影到低维空间,突出热模式。这将提高热系统的可靠性,从而有助于 CBE。结合临床信息和人口统计数据的嵌入方法使用随机森林的最佳结果为 82.9%(66.7%,86.7%)。这些结果显示了良好的初步效果,有助于早期发现乳腺异常,并可作为一种非侵入性工具来辅助 CBE。
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引用次数: 0
Comparison of Inductive Thermography and Computer Tomography Results for Short Surface Cracks 短表面裂缝的感应热成像和计算机断层扫描结果比较
Pub Date : 2023-11-14 DOI: 10.3390/engproc2023051036
B. Oswald-Tranta
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引用次数: 0
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The 17th International Workshop on Advanced Infrared Technology and Applications
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