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Rizkalla, J., Tilbury, W., Helmy, A., Rizkalla, M., Suryadevara, V.K. and Holdmann, M.M. (2015) Computer Simulation/Practical Models for Human Thyroid Thermographic Imaging. Journal of Biomedical Science and Engineering, 8, 246-256.
https://doi.org/10.4236/jbise.2015.84024

has been cited by the following article:

• TITLE: High Sensitive Graphene Devices for Non-Invasive Early Diagnosis of Hyperthyroidism: A Feasibility Study

  AUTHORS: Avinash Yadav, Inayeth Ali, Ahdy Helmy, Maher Rizkalla

  KEYWORDS: Diagnosis, Non-Invasive, GNRFET, Thermography, Ultrasonography, IoT

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.12 No.12, December 16, 2019

  ABSTRACT: This paper presents a novel approach with Graphene devices that are highly sensitive in detecting IR energy. Current non-imaging techniques like ultrasonography have been proposed for thyroid diagnosis with limitations on ability to detect low-temperature distribution around the hot spot at the starting stage of the thyroid hyperthyroidism. The energy distribution around hotspot is minimal at the beginning stage. This detection may require ultra-high sensitive materials to the IR energy. A computer modeling using COMSOL software shows the thermal energy simulation of a thyroid gland with single or multiple active nodules. Data collection of the energy levels and condition of thyroid in the human body support the work investigated in this study. The study conducted here has shown as low as 0.1 - 5 mW IR power can be detected based on the Graphene device sensitivity. The paper details the simulation and approach for this non-invasive diagnosis.