Investigation of a Graphene-Based Optical Sensor Integrated with the Chan-Vese Method for Cancer Detection

Currently, the diagnosis of Laryngeal Squamous Cell Carcinoma (LSCC) is predominantly conducted through videoendoscopy. Despite technological progress in this field, it is important to highlight that this method is still characterized by its invasive and subjective nature. The scope of this study focuses on the design and implementation of a graphene-based optical sensor, aiming to improve the diagnostic accuracy of LSCC. The proposed sensor is made using consolidated MEMS techniques, being integrated with a detection algorithm based on the segmentation of endoscopic images. Using graphene as a light modulating element, the sensor quantifies and identifies the LSCC in a different way. The results obtained in this study reveal that the integrated sensorpresents an innovative and more accurate approach compared to methods documented in scientific literature. This promisinginnovation has the potential to simplify endoscopic procedures, significantly contributing to advancements in thediagnosis and treatment of Laryngeal Squamous Cell Carcinoma.