JBiSE  Vol.8 No.4 , April 2015
Computer Simulation/Practical Models for Human Thyroid Thermographic Imaging
Abstract: We have demonstrated a successful computer model utilizing ANSIS software that is verified with a practical model using Infrared (IR) sensors. The simulation model incorporates the three heat transfer coefficients: conduction, convection, and radiation. While the conduction component was a major contributor to the simulation model, the other two coefficients have added to the accuracy and precision of the model. Convection heat allows for the influence of blood flow within the study, while the radiation aspect, sensed through IR sensors, links the practical model of the study. This study also compares simulation data with the applied model generated from IR probe sensors. These sensors formed an IR scanner that moved via servo mechanical system, tracking the temperature distribution within and around the thyroid gland. These data were analyzed and processed to produce a thermal image of the thyroid gland. The acquired data were then compared with an Iodine uptake scan for the same patients.
Cite this paper: Rizkalla, J. , Tilbury, W. , Helmy, A. , Suryadevara, V. , Rizkalla, M. and Holdmann, M. (2015) Computer Simulation/Practical Models for Human Thyroid Thermographic Imaging. Journal of Biomedical Science and Engineering, 8, 246-256. doi: 10.4236/jbise.2015.84024.

[1]   Al Khatib, I., Poletti, F., Bertozzi, D., Benini, L., Bechara, M., Khalifeh, H., Jantsch, A. and Nabiev, R. (2006) A Multiprocessor System-on-Chip for Real-Time Biomedical Monitoring and Analysis: Architectural Design Space Exploration. Design Automation Conference, 125-130.

[2]   Imntyernational Atomic Energy Agency (IAEA) (2009) Nuclear Medicine in Thyroid Cancer Management: A Practical Approach.

[3]   Hopkins, C.R. and Reading, C.C. (1995) Thyroid and Parathyroid Imaging. Seminars in Ultrasound, CT and MRI, 16, 279-295.

[4]   Bagavathiappan, S., Saravanan, T., Philip, J., Jayakumar, T., Raj, B., Karunanithi, R., Panicker, T.M.R., Korath, M.P. and Jagadeesan, K. (2009) Infrared Thermal Imaging for Detection of Peripheral Vascular Disorders. Journal of Medical Physics, 34, 43-47.

[5]   Bagavathiappan, S., Saravanan, T., Philip, J., Jayakumar, T., Raj, B., Karunanithi, R., Korath, P. and Jagadeesan, K. (2008) Investigation of Peripheral Vascular Disorders Using Thermal Imaging. The British Journal of Diabetes & Vascular Disease, 8, 102-104.

[6]   Schaefer, G., Zavisek, M. and Nakashima, T. (2009) Thermography Based Breast Cancer Analysis Using Statistical Features and Fuzzy Classification. Pattern Recognition, 42, 1133-1137.

[7]   Dai, H., Omer, A.M. and Jiang, G. (2008) The Attempt of Breast Thermography Processing Applying with ITE. IEEE EMBS International Conference on Information Technology Applications in Biomedicine, Shenzhen, 30-31 May 2008, 160-163.

[8]   Dodde, R., Shih, A. and Advincula, A.P. (2009) A Novel Technique for Demonstrating the Real-Time Subsurface Tissue Thermal Profile of Two Energized Surgical Instruments. Journal of Minimally Invasive Gynecology, 16, 599-603.

[9]   Kateb, B., Yamamoto, V., Yu, C., Grundfest, W. and Gruen, J.P. (2009) Infrared Thermal Imaging: A Review of the Literature and Case Report. Journal of Neuroimage, 47, T154-T162.

[10]   Helmy, A., Holdmann, M. and Rizkalla, M. (2008) Application of Thermography for Non-Invasive Diagnosis of Thyroid Gland Disease. IEEE Transactions on Biomedical Engineering, 55, 1168-1175.

[11]   Kreith, F. (1973) Principles of Heat Transfer. 3rd Edition, Intext, New York, 607-608.