Graphene Based-Sensor for Basal Cell Carcinoma Detection

We propose and analyze a novel type of graphene-based device by using an improved anisotropic wave concept iterative process (WCIP) algorithm, this device can operate as a tunable electronic and magnetic sensor for Basal Cell Carcinoma (BCC) detection at the terahertz band. The proposed sensor consists of a planar filter, and a sample holder is located in the middle of it, to hold the normal skin and BCC samples. Through the proposed modeling approach of the biological samples, we can integrate the healthy and BCC tissues into this algorithm by redefining their boundary condition in terms of waves, this procedure was done without involving any volumetric discretization. At the beginning, we validate the effectiveness of the proposed anisotropic WCIP algorithm, an excellent agreement has been obtained, which demonstrate a high precision of the proposed algorithm. Finally, the numerical simulations demonstrate that the sensor has the ability to discover the healthy tissue with a high sensitivity of 6.9
THz/RIU
and Basal Cell Carcinoma with 11.2
THz/RIU
.