Three-dimensional modelling and terahertz imaging of malignant cells with convolutional time-reversed FDTD method
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2022
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Abstract
A novel image reconstruction approach to terahertz pulsed imaging for detecting malignant and fibrous cells within healthy tissue is presented. The non-ionizing effect of the terahertz radiation on healthy tissue makes it a future diagnosis method in medical imaging. The implemented method is based on the convolutional time-reversed FDTD algorithm in the terahertz range. It is computationally efficient and accurately reconstructs images of malignancies from reflected terahertz signals. Besides, the technique is capable of differentiating malignant, fibrous, and fatty cells through the variations of their electrical properties at the terahertz frequency range and well reconstructing their images in 3D. The images created in this method are in high resolution, even for cell-sized malignancies. Furthermore, the proposed technique is compared with conventional terahertz imaging methods and found to have more sophisticated outcomes. © 2022 Taylor & Francis.
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Cells , Cytology , Diagnosis , Finite difference time domain method , Image reconstruction , Medical imaging , Terahertz waves , Three dimensional computer graphics , Tissue , Cancer detection , Cell model , Healthy tissues , Malignant cell modeling , Malignant cells , Novel image reconstruction , Terahertz imaging , Three dimensional modelling , Time reversed FDTD , Time-reversed , Convolution