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A Deep Study on Thermography Methods and Applications in Assessment of Various Disorders

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Artificial Intelligence for Smart Healthcare

Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

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Abstract

A thermography is an untroublesome and paraclinical examination process deprived of irradiation that concludes medical, practical analysis and comprises measurement in heat that emanates under different regions of the body employing an instrument having an inbuilt sensor for detecting the infrared radiation (IR) in the electromagnetic spectrum. It stood as hopeful equipment for diagnostics at early stages because of the high resolution and sensitivity employed thermal cameras are accessible. The various disorders the assessment is associated with are the temporomandibular disorders (TMD) that affect the temporomandibular joints (TMJ), the neck muscles, and masticatory muscles. From the measurements taken within the time of fewer than 2 min of the various positions of seating, static and dynamic with required images, the temperature at the facial area can be determined effortlessly. Based on the utilized therapeutic approaches, the exactness and the reliability of the thermograms are highly significant. This paper reviews various methods involved in thermography and evaluation of different kinds of disorders in specific applications. An object’s temperature has a significant influence on the amount of infrared radiation it emits. This characteristic of infrared thermography is utilized in various applications, including medical diagnostics, mechanical and electrical maintenance, and as a heat loss indicator in buildings. Using infrared thermography-based sensors, this article examines the current state of infrared thermography, emphasising temperature measurement and non-destructive testing. A general introduction to infrared thermography and the common procedures for temperature measurement and non-destructive testing are presented. Furthermore, developments in these fields and recent advances are reviewed. This work provided an accuracy of 98.67% and a sensitivity of 94.45%, and a recall of 92.34% had been attained.

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References

  1. D. Sabbagh Haddad, M. L. Brioschi, “Oral Healt care and Technologies” Information Resources Management Association, USA, Chapter 3, pp. 329–350, (2016).

    Google Scholar 

  2. Dionisio, A., Roseiro, L., Fonseca, J., & Nicolau, P. Thermography Evaluation on Facial Temperature Recovery after Elastic Gum. International Journal of Biomedical and Biological Engineering, 11(5), 269–273, (2017).

    Google Scholar 

  3. Ahammad, S. H., Rajesh, V., Rahman, M. Z. U., & Lay-Ekuakille, A. A hybrid CNN-based segmentation and boosting classifier for real time sensor spinal cord injury data. IEEE Sensors Journal, 20(17), 10092–10101, (2020).

    Article  Google Scholar 

  4. Ahammad, S. H., Rajesh, V., & Rahman, M. Z. U. Fast and accurate feature extraction-based segmentation framework for spinal cord injury severity classification. IEEE Access, 7, 46092–46103 (2019).

    Article  Google Scholar 

  5. Ahammad, S. K., & Rajesh, V. Image processing based segmentation techniques for spinal cord in MRI. Indian Journal of Public Health Research & Development, 9(6), (2018).

    Google Scholar 

  6. Ahammad, S. H., Rajesh, V., Neetha, A., Sai Jeesmitha, B., & Srikanth, A. Automatic segmentation of spinal cord diffusion MR images for disease location finding. Indonesian Journal of Electrical Engineering and Computer Science, 15(3), 1313–1321 (2019).

    Article  Google Scholar 

  7. Vijaykumar, G., Gantala, A., Gade, M. S. L., Anjaneyulu, P., & Ahammad, S. H. Microcontroller based heartbeat monitoring and display on PC. Journal of Advanced Research in Dynamical and Control Systems, 9(4), 250–260, (2017).

    Google Scholar 

  8. Inthiyaz, S., Prasad, M. V. D., Lakshmi, R. U. S., Sai, N. S., Kumar, P. P., & Ahammad, S. H. Agriculture based plant leaf health assessment tool: A deep learning perspective. International Journal of Emerging Trends in Engineering Research, 7(11), 690–694, (2019).

    Article  Google Scholar 

  9. Kumar, M. S., Inthiyaz, S., Vamsi, C. K., Ahammad, S. H., Sai Lakshmi, K., Venu Gopal, P., & Bala Raghavendra, A. Power optimization using dual SRAM circuit. International Journal of Innovative Technology and Exploring Engineering, 8(8), 1032–1036, (2019).

    Google Scholar 

  10. Ahammad, S. H., Rajesh, V., Hanumatsai, N., Venumadhav, A., Sasank, N. S. S., Gupta, K. B., & Inithiyaz, S. MRI image training and finding acute spine injury with the help of hemorrhagic and non-hemorrhagic rope wounds method. Indian Journal of Public Health Research & Development, 10(7), 404, (2019).

    Article  Google Scholar 

  11. Siva Kumar, M., Inthiyaz, S., Venkata Krishna, P., Jyothsna Ravali, C., Veenamadhuri, J., Hanuman Reddy, Y., & Hasane Ahammad, S. Implementation of most appropriate leakage power techniques in vlsi circuits using nand and nor gates. International Journal of Innovative Technology and Exploring Engineering, 8(7), 797–801 (2019).

    Google Scholar 

  12. Myla, S., Marella, S. T., Goud, A. S., Ahammad, S. H., Kumar, G. N. S., & Inthiyaz, S. Design decision taking system for student career selection for accurate academic system. Journal of Scientific & Technology Research, 8(9), 2199–2206 (2019).

    Google Scholar 

  13. Raj Kumar, A., Kumar, G. N. S., Chithanoori, J. K., Mallik, K. S. K., Srinivas, P., & Hasane Ahammad, S. Design and analysis of a heavy vehicle chassis by using E-glass epoxy & S-2 glass materials. International Journal of Recent Technology and Engineering, 7(6), 903–905 (2019).

    Google Scholar 

  14. Madhav, B. T. P., & Anilkumar, T. Design and study of multiband planar wheel-like fractal antenna for vehicular communication applications. Microwave and Optical Technology Letters, 60(8), 1985–1993 (2018).

    Article  Google Scholar 

  15. Deepak, B. S., Madhav, B. T., Prabhakar, V. S. V., Lakshman, P., Anilkumar, T., & Rao, M. V. Design and analysis of hetero triangle linked hybrid web fractal antenna for wide band applications. Progress in Electromagnetics Research C, 83, 147–159 (2018).

    Google Scholar 

  16. Madhav, B. T. P., Rao, T. V., & Anilkumar, T. Design of 4-element printed array antenna for ultra-wideband applications. International Journal of Microwave and Optical Technology, 13(1), 8–17 (2018).

    Google Scholar 

  17. Gattim, N. K., Pallerla, S. R., Bojja, P., Reddy, T. P. K., Chowdary, V. N., Dhiraj, V., & Ahammad, S. H. Plant leaf disease detection using SVM technique. International Journal of Emerging Trends in Engineering Research, 7(11), 634–637 (2019).

    Article  Google Scholar 

  18. Ahammad, S. H., Rajesh, V., Venkatesh, K. N., Nagaraju, P., Rao, P. R., & Inthiyaz, S. Liver segmentation using abdominal CT scanning to detect liver disease area. International Journal of Emerging Trends in Engineering Research, 7(11), 664–669 (2019).

    Article  Google Scholar 

  19. Diniz de Lima E, Souza Paulino JA, Lira de Farias Freitas AP, Viana Ferreira JE, Barbosa JDS, Bezerra Silva DF, Bento PM, Araújo Maia Amorim AM, Melo DP. Artificial intelligence and infrared thermography as auxiliary tools in the diagnosis of temporomandibular disorder. Dentomaxillofac Radiol. 2021 Oct 6:20210318 (2021).

    Google Scholar 

  20. Snekhalatha Umapathy, Palani Thanaraj Krishnan, “Automated detection of orofacial pain from thermograms using machine learning and deep learning approaches” Expert Systems, Volume 38, Issue 7 (2021).

    Google Scholar 

  21. Tsolaki, E., Gladiol Zenunaj, Edo Gresta, Stefano Di Mase, and Francesco Mascoli. “Contrast-Enhanced Ultrasound versus Computed Tomography Angiography in the Follow-Up of the Treatment of Abdominal Aortic Aneurysm with Endovascular Techniques.” Journal for Vascular Ultrasound 36, no. 4: 263–66 (2012).

    Google Scholar 

  22. B. Panjwani, V. Singh, A. Rani, and V. Mohan, “Optimum multi-drug regime for compartment model of tumour: cell-cycle-specific dynamics in the presence of resistance,” Journal of Pharmacokinetics and Pharmacodynamics, vol. 48, no. 4, pp. 543–562, (2021).

    Article  Google Scholar 

  23. D. K. Sharma, B. Singh, E. Herman, R. Regine, S. S. Rajest and V. P. Mishra, “Maximum Information Measure Policies in Reinforcement Learning with Deep Energy-Based Model,” 2021 International Conference on Computational Intelligence and Knowledge Economy, pp. 19–24 (2021).

    Google Scholar 

  24. D. K. Sharma, B. Singh, M. Raja, R. Regin and S. S. Rajest, “An Efficient Python Approach for Simulation of Poisson Distribution,” 2021 7th International Conference on Advanced Computing and Communication Systems, pp. 2011–2014 (2021).

    Google Scholar 

  25. D. S. Q. Al-Yasiri and A. J. Obaid, “A New Approach for Object Detection, Recognition and Retrieving in Painting Images,” Journal of Advance Research in Dynamic and Control System, vol. 10, no. 2, pp. 2345–2359, (2018).

    Google Scholar 

  26. T. A. Al-asadi and A. J. Obaid, “Object detection and recognition by using enhanced speeded up robust feature,” International Journal of Computer Science and Network Security, vol. 16, no. 4, pp. 66–71, (2016).

    Google Scholar 

  27. F. Arslan, B. Singh, D. K. Sharma, R. Regin, R. Steffi and S. Suman Rajest, “Optimization Technique Approach to Resolve Food Sustainability Problems,” 2021 International Conference on Computational Intelligence and Knowledge Economy, pp. 25–30, (2021).

    Google Scholar 

  28. F. J. J. Joseph, “Effect of supervised learning methodologies in offline handwritten Thai character recognition,” Int. J. Inf. Technol., vol. 12, no. 1, pp. 57–64, Mar. (2020),

    Google Scholar 

  29. F. J. John Joseph, R. T, and J. J. C, “Classification of correlated subspaces using HoVer representation of Census Data,” in 2011 International Conference on Emerging Trends in Electrical and Computer Technology, pp. 906–911 (2011).

    Google Scholar 

  30. G. A. Ogunmola, B. Singh, D. K. Sharma, R. Regin, S. S. Rajest and N. Singh, “Involvement of Distance Measure in Assessing and Resolving Efficiency Environmental Obstacles,” 2021 International Conference on Computational Intelligence and Knowledge Economy, pp. 13–18 (2021).

    Google Scholar 

  31. Ghai, D., Gianey, H. K., Jain, A., & Uppal, R. S. Quantum and dual-tree complex wavelet transform-based image watermarking. International Journal of Modern Physics B, 34(04), 2050009 (2020).

    Google Scholar 

  32. Ishaq, A., Sadiq, S., Umer, M., Ullah, S., Mirjalili, S., Rupapara, V., & Nappi, M. Improving the Prediction of Heart Failure Patients’ Survival Using SMOTE and Effective Data Mining Techniques. IEEE Access, 9, 39707–39716 (2021).

    Article  Google Scholar 

  33. J. Kubiczek and B. Hadasik, “Challenges in Reporting the COVID-19 Spread and its Presentation to the Society,” J. Data and Information Quality, vol. 13, no. 4, pp. 1–7, (2021).

    Article  Google Scholar 

  34. Jain, A., & Kumar, A. Desmogging of still smoggy images using a novel channel prior. Journal of Ambient Intelligence and Humanized Computing, 12(1), 1161–1177 (2021).

    Article  Google Scholar 

  35. K. Ganesh Kumar and S. Sudhakar, Improved Network Traffic by Attacking Denial of Service to Protect Resource Using Z-Test Based 4-Tier Geomark Traceback (Z4TGT), Wireless Personal Communications, Vol. 114, No. 4, pp:3541–3575, (2020).

    Google Scholar 

  36. K. Jayanthi, R. Rathinam and S. Pattabhi, “Electrocoagulation treatment for removal of Reactive Blue 19 from aqueous solution using Iron electrode”, Research Journal of Life Sciences, Bioinformatics, Pharmaceutical and Chemical Sciences, 4:2, 101–113 (2018).

    Google Scholar 

  37. Kumar, S., Jain, A., Shukla, A. P., Singh, S., Raja, R., Rani, S., … & Masud, M. A Comparative Analysis of Machine Learning Algorithms for Detection of Organic and Nonorganic Cotton Diseases. Mathematical Problems in Engineering, (2021).

    Google Scholar 

  38. M. Govindaraj, R. Rathinam, C. Sukumar, M. Uthayasankar and S. Pattabhi, “Electrochemical oxidation of bisphenol-A from aqueous solution using graphite electrodes,” Environmental Technology 34:4, 503–511 (2013).

    Google Scholar 

  39. N. O. alkaam, D. M. Q. Mohammed and A. J. Obaid, “A Hybrid Technique for Object Detection and Recognition Using Local Features Algorithms,” Journal of Advance Research in Dynamical and Control Systems, vol. 10, no. 2, pp. 2330–2343, (2018).

    Google Scholar 

  40. Nomani, M. & Parveen, R. Legal Connotations of Biological Resources and its Ripple effect on Conservation Research in India and abroad, International Journal of Conservation Science. Vol. 12 Issue 2, 571–576 (2021).

    Google Scholar 

  41. Prabhu Kavin, B., Ganapathy, S., Suthanthiramani, P., & Kannan, A. A modified digital signature algorithm to improve the biomedical image integrity in cloud environment. Advances in Computational Techniques for Biomedical Image Analysis, 253–271 (2020).

    Google Scholar 

  42. Procházka A, Charvátová H, Vyšata O, Kopal J, Chambers J. Breathing Analysis Using Thermal and Depth Imaging Camera Video Records. Sensors (Basel). 2017 Jun 16;17(6):1408 (2017).

    Google Scholar 

  43. R. Rathinam, M. Govindaraj, K. Vijayakumar and S. Pattabhi “Removal of Colour from Aqueous Rhodamine B Dye Solution by Photo electrocoagulation Treatment Techniques”, “Journal of Engineering, Scientific Research and Application”, 1: 2, 80–89 (2015).

    Google Scholar 

  44. Rehana Parveen. Impact of anti-money laundering legislation in the United Kingdom and European Union. International Journal of Economics and Management Systems, 5, 118–122, (2020).

    Google Scholar 

  45. Rustam, F., Khalid, M., Aslam, W., Rupapara, V., Mehmood, A., & Choi, G. S. A performance comparison of supervised machine learning models for Covid-19 tweets sentiment analysis. PLOS ONE, 16(2) (2021), e0245909.

    Google Scholar 

  46. S. Bhoumik, S. Chatterjee, A. Sarkar, A. Kumar, and F. J. John Joseph, “Covid 19 Prediction from X Ray Images Using Fully Connected Convolutional Neural Network,” in CSBio ’20: Proceedings of the Eleventh International Conference on Computational Systems-Biology and Bioinformatics, pp. 106–107 (2020).

    Google Scholar 

  47. S. Sudhakar and S. Chenthur Pandian “Authorized Node Detection and Accuracy in Position-Based Information for MANET”, European Journal of Scientific Research, Vol. 70, No. 2, pp. 253–265, (2012).

    Google Scholar 

  48. Sadiq, S., Umer, M., Ullah, S., Mirjalili, S., Rupapara, V., & NAPPI, M. Discrepancy detection between actual user reviews and numeric ratings of Google App store using deep learning. Expert Systems with Applications, 115111 (2021).

    Google Scholar 

  49. Sharma, S. K., Jain, A., Gupta, K., Prasad, D., & Singh, V. An internal schematic view and simulation of major diagonal mesh network-on-chip. Journal of Computational and Theoretical Nanoscience, 16(10), 4412–4417 (2019).

    Article  Google Scholar 

  50. V. Mohan, H. Chhabra, A. Rani, and V. Singh, “An expert 2DOF fractional order fuzzy PID controller for nonlinear systems,” Neural Computing and Applications, vol. 31, no. 8, pp. 4253–4270, (2019).

    Google Scholar 

  51. Yousaf, A., Umer, M., Sadiq, S., Ullah, S., Mirjalili, S., Rupapara, V., & Nappi, M. Emotion Recognition by Textual Tweets Classification Using Voting Classifier (LR-SGD). IEEE Access, 9, 6286–6295 (2021).

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of CSE, Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India

    Komali Dammalapati

  2. Department of ECE, Vignan’s Institute of Information Technology (A) Duvvada, Visakhapatnam, Andhra Pradesh, India

    P. S. N. Murty

  3. Department of Electronics and Communication Engineering, B V Raju Institute of Technology, Narsapur, India

    Ibrahim Patel

  4. CSE Department, S B Jain Institute of Technology Management and Research, Nagpur, India

    Prabha Shreeraj Nair

  5. Department of ECE, Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India

    K. Saikumar

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  1. Komali Dammalapati
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  2. P. S. N. Murty
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  3. Ibrahim Patel
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  4. Prabha Shreeraj Nair
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  5. K. Saikumar
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Editor information

Editors and Affiliations

  1. Computer Science and Engineering, Jamia Hamdard, New Delhi, India

    Parul Agarwal

  2. Delhi Skill and Entrepreneurship University, Dwarka, Delhi, India

    Kavita Khanna

  3. Faculty of Computers and Artificial Intelligence, Beni-Suef University, Beni-Suef City, Egypt

    Ahmed A Elngar

  4. Faculty of Computer Science and Mathematics, University of Kufa, Najaf, Iraq

    Ahmed J. Obaid

  5. Jan Wyzykowski University, Polkowice, Poland

    Zdzislaw Polkowski

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Dammalapati, K., Murty, P.S.N., Patel, I., Nair, P.S., Saikumar, K. (2023). A Deep Study on Thermography Methods and Applications in Assessment of Various Disorders. In: Agarwal, P., Khanna, K., Elngar, A.A., Obaid, A.J., Polkowski, Z. (eds) Artificial Intelligence for Smart Healthcare. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-23602-0_21

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  • DOI: https://doi.org/10.1007/978-3-031-23602-0_21

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