A Low Cost Thermal Imaging System for Medical Diagnostic Applications

  • Abstract
  • Keywords
  • References
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  • Abstract

    This paper presents a low cost thermal imaging system for medical diagnostic applications. Available systems are expensive and are mostly meant for industrial applications. In this paper the existing system which is a basic system consisting of thermopile based sensor which produces thermal array is replaced with a “Thermal Imaging Camera” for medical diagnosis applications. The thermal camera scans the entire body of the individual to diagnose the diseases ie, infrared radiations from the human body part and then converts them to electronic signal. If there is any lump or any other unusual change inside the body, then the body temperature at that particular part will alone be high or low which indicates the “Hypo” or “Hyper” condition of the disease. Scene captured by the thermal camera is represented as a matrix. Each element of matrix represents a temperature value. Temperature values are divided into different ranges and each range is represented by an RGB value by the Raspberry Pi.  Based on this thermal camera image we can detect the exact location in individual body part and further for that part alone we can take test and detect what kind of disease the individual is suffering. This system can be used in wide applications in the field of medicine such as detection of breast cancer, fever screening, thyroid disease detection, early detection of risk for diabetic peripheral neuropathy, Reynaud’s phenomenon, orthopedics etc.



  • Keywords

    Thermography, thermogram, thermal imaging system, AMG8833 camera, raspberry pi, pseudo color image.

  • References

      [1] Sruthi S & Sasikala M, “A Low Cost Thermal Imaging System for Medical Diagnostic Applications”, International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials, (2015), pp.621-623.

      [2] Helmy A, Holdmann M & Rizkalla M, “Application of thermography for non-invasive diagnosis of thyroid gland disease”, IEEE transactions on biomedical engineering, Vol.55, No.3, (2008), pp.1168-1175.

      [3] Marques RS, Conci A, Pérez MG, Andaluz VH & Mejía TM, “An Approach for Automatic Segmentation of Thermal Images in Computer Aided Diagnosis”, IEEE Latin America Transactions, Vol.14, No.4, (2016).

      [4] Diakides NA & Bronzino JD, Medical Infrared Imaging, CRC Press, (2012).

      [5] Dulski R, Sosnowski T, Piątkowski T & Milewski S, “Evaluation of hardware implementation of the infrared image enhancement algorithm”, 11th International Conference on Quantitative Infra Red Thermography, (2012).

      [6] Iven G, Chekh V, Luan S, Mueen A, Soliz P, Xu W & Burge M, “Non-contact Sensation Screening of Diabetic Foot Using Low Cost Infrared Sensors”, IEEE 27th International Symposium Computer-Based Medical Systems (CBMS), (2014), 479-480.

      [7] Kaplan, H “Practical Applications of Infrared Thermal Sensing and Imaging Equipment”, SPIE Tutorial Text, (2007), pp.20-25.

      [8] Lahiri BB, Bagavathiappan S, Jayakumar T & Philip J, “Medical applications of infrared thermography: A review”, Infrared Physics & Technology, ELSEVIER, Vol.55, (2012), pp.221-235.

      [9] Aweda MA, Adeyomoye AO & Abe GA, “Thermographic analysis of thyroid diseases”, Adv. Appl. Sci. Res., Vol.3, (2012), pp.2027-2032.

      [10] Arora N, Martins D, Ruggerio D, Tousimis E, Swistel AJ, Osborne MP & Simmons RM, “Effectiveness of a noninvasive digital infrared thermal imaging system in the detection of breast cancer”, American Journal of Surgery, Vol.196, No.4,(2008), pp.523-526.

      [11] Bagavathiappan S, Saravanan T, Philip J, Jayakumar T, Raj B, Karunanithi R, Panicker TMR, Korath MP & Jagadeesan K, “Infrared Thermal Imaging for Detection of Peripheral Vascular Disorders”, Journal of medical physics/Association of Medical Physicists of India, Vol.34, No.1,(2009).

      [12] Carmeliet P & Jain RK, “Angiogenesis in cancer and other diseases”, Nature, Vol.407, (2000), pp.249 –57.

      [13] Cheriguene S, Azizi N, Zemmal N, Dey N, Djellali H & Farah N, “Optimized Tumor Breast Cancer Classification Using Combining Random Subspace and Static Classifiers Selection Paradigms”, Applications of Intelligent Optimization in Biology and Medicine, (2016), pp.289-307.

      [14] Davis AP & Lettington AH, “Principles of thermal imaging”, Applications of thermal imaging, (1988).

      [15] Jones BF & Plassmann P, “Digital infrared thermal imaging of human skin”, IEEE Engineering in Medicine and Biology Magazine, Vol.21, No.6,(2002), pp.41-48.

      [16] Ring F, “Thermal imaging today and its relevance to diabetes”, Journal of diabetes science and technology, Vol.4, No.4,(2010), pp.857-862.

      [17] A Akhmetbekova, P Auyesbayeva, Sh Ibrayev (2018). Turkic "Hikaya" genre and its characters. Opción, Año 33. 81-106.

      [18] A Mukanbetkaliyev, S Amandykova, Y Zhambayev, Z Duskaziyeva, A Alimbetova (2018). The aspects of legal regulation on staffing of procuratorial authorities of the Russian Federation and the Republic of Kazakhstan Opción, Año 33. 187-216.




Article ID: 17897
DOI: 10.14419/ijet.v7i3.27.17897

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