Multispectral terahertz and autofluorescence imaging for tumor classification in breast and oral fresh tissue

Jyotirmayee Dash; Geethanjali Radhakrishnan; Arun Jana; Lenin B.; Shyamsunder Mandayam; Bala Pesala

doi:10.1117/12.3003955

13 March 2024 Multispectral terahertz and autofluorescence imaging for tumor classification in breast and oral fresh tissue

Jyotirmayee Dash, Geethanjali Radhakrishnan, Arun Jana, Lenin B., Shyamsunder Mandayam, Bala Pesala

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Proceedings Volume PC12834, Multimodal Biomedical Imaging XIX; PC128340D (2024) https://doi.org/10.1117/12.3003955
Event: SPIE BiOS, 2024, San Francisco, California, United States

Abstract

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, and 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

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KEYWORDS

Cancer

Tissues

Auto-fluorescence imaging

Breast

Evolutionary algorithms

Terahertz technology

Tumors

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