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.
In this paper, Continuous Wave Terahertz system is utilized to image freshly excised oral and breast tissues. The THz images show significant contrast between tumour and adjacent normal/fat tissues in both breast and oral cancer. The obtained images are compared with the histopathology images for the confirmation. Advanced Artificial Intelligence algorithm is developed in which the THz images at each pixel is labelled based on overlapping of THz and pathology images. The results demonstrate the potential of low frequency THz imaging to differentiate benign and malignant tissue in freshly excised samples.
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