ITO-based multi-band metasurface absorber for early detection of hepatic cancer through deep learning

This study introduces a multi-band metasurface absorber, optimized for high-sensitivity detection of hepatic (liver) cancer. The unit cell comprises a top ITO sheet with several "+" - shaped slots, in which a graphene layer is incorporated into the central slot. This layer is attached to a quartz glass substrate to provide optical clarity, while a continuous ITO ground layer is used to mitigate electromagnetic (EM) transmission. Simulation results indicate that the structure attains exceptional absorption of 95%, 99%, 96%, and 94% at 0.594 (f₁), 0.988 (f₂), 1.196 (f₃), and 1.518 (f₄) THz, respectively. Electric field distribution and an equivalent electric circuit (EEC) analysis are used to theoretically analyze and confirm the resonance properties and physical operating mechanism. Furthermore, the proposed multi-band metasurface absorber demonstrates a sensitivity of 36 GHz/RIU, a Figure of Merit (FOM) of 2045 RIU^-1, and a quality factor (Q-factor) of 70, thereby enabling reliable and precise detection of minor refractive index fluctuations associated with hepatic cancer biomarkers. To improve diagnostic accuracy, a deep learning (DL) analysis framework is used to distinguish cancerous hepatic tissues. The model demonstrates 99.9% accuracy on the training data, with a validation accuracy of 98.7%. Owing to its multi-band adaptability and DL-driven enhanced detection accuracy, the proposed work provides a revolutionary foundation for next-generation visually accessible oncological diagnostics and advanced biomedical imaging.