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Terahertz and autofluorescence imaging technologies are combined for accurate breast and oral cancer margin detection. More than thirty fresh tissue samples are imaged in this study. Cancer progression causes structural, and metabolic changes which can be probed effectively by combining Terahertz and Autofluorescence technologies and using advanced machine learning algorithms. To train the Machine Learning algorithm, the cancer and noncancer regions in Terahertz and fluorescence images are identified by overlapping with histopathology images. This study confirms that the combination of multiple spectroscopy techniques and Machine Learning algorithms has the potential to achieve better diagnostic accuracy in fresh cancer tissue.
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Jyotirmayee Dash, Geethanjali Radhakrishnan, Arun Jana, Lenin B., Shyamsunder Mandayam, Bala Pesala, "Multispectral terahertz and autofluorescence imaging for tumor classification in breast and oral fresh tissue," Proc. SPIE PC12834, Multimodal Biomedical Imaging XIX, PC128340D (13 March 2024); https://doi.org/10.1117/12.3003955