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We suggest a method for biomedical imaging with heat in the far infrared spectrum using principal and independent components analysis. This method produces novel results suggesting physiologic mechanisms of considerable importance for diagnostic imaging. When using thermal imaging to detect breast cancer the dominant heat signature is of indirect heat transported by the blood away from the tumor location into the skin. Interpretation is usually based on vascular angiogenesis and not by observing the direct cancerous heat. In this new method one uses sequence of thermal images of the patient breast following external temperature change. Data is recorded and analyze using independent component analysis (ICA) and principal component analysis (PCA). ICA separate the images sequence into new independent images having common characteristic time behavior. Using the Brazilian visual lab mastology data set we observed three type of images: Images corresponding to minimum change as function of applied temperature or time which are associate with the cancer generated heat, images which shows moderate temperature dependent and are associate with veins affected by vasomodulation and images that shows complex time behavior indicating heat absorption by high perfusion of the tumor. All components are clear and distinct.
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Meir Gershenson, Jonathan Gershenson, "Use of components analysis to identify internal heat in breast dynamic thermal images," Proc. SPIE 12109, Thermosense: Thermal Infrared Applications XLIV, 121090K (27 May 2022); https://doi.org/10.1117/12.2612283