Mr. Leonardo D. Buitrago Profile

Leonardo D. Buitrago

at Univ of Maryland College Park

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Proceedings Article | 12 June 2023 Poster + Paper

Optimal thermomic biomarkers for early diagnosis of breast cancer

Leonardo Buitrago, Jimmy Azarnoosh, Xavier P. V. Maldague, Bardia Yousefi

Proceedings Volume 12536, 1253611 (2023) https://doi.org/10.1117/12.2663835

KEYWORDS: Breast cancer, Thermography, Breast, Matrices, Thermal modeling, Cancer detection, Mammography, Principal component analysis, Cancer, Tissues

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Dynamic thermography is a well-established diagnostic tool for breast cancer screening that can be used in conjunction with mammography and clinical breast examination (CBE). Thermographic imaging biomarkers, known as thermomics, have been shown to detect vasodilation in breast tissue, indicating abnormalities and lesions. Heterogeneous thermal patterns also reveal angiogenesis or the formation of new blood vessels. This study applied thermal imaging biomarkers, and thermographic imaging, for breast cancer screening. We applied two low rank embedding approaches, Gaussian and Bell embedding, to obtain the optimal thermomics with the help of elbow method, which resulted in finding breast thermal heterogeneity. Non-negative Matrix Factorization (NMF) was used to create a low-ranked representation of thermal images. High dimensional radiomics and thermomics were then extracted, and feature abundance was reduced using spectral clustering. The best results of the Deep semiNMF with Bell embedding method combining clinical information and demographics yield 81.6% (±3.9%). The model was trained with constant hyperparameters setting across the comparison to predict abnormality, and the results demonstrated promising preliminary performance. Optimal biomarkers have the potential to preserve thermal heterogeneity, leading to early detection of breast cancer, and can serve as a non-invasive tool to aid CBE. Codes corresponded with this proceeding can be found at the following GitHub repository: https://github.com/BardiaYo/SPIEThermosense2023.git

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