Skip to main content
SpringerLink
Log in

A novel image processing procedure for thermographic image analysis

  • Original Article
  • Published:
Medical & Biological Engineering & Computing Aims and scope Submit manuscript

Abstract

The imaging procedure shown in this paper has been developed for processing thermographic images, measuring the ocular surface temperature (OST) and visualizing the ocular thermal maps in a fast, reliable, and reproducible way. The strength of this new method is that the measured OSTs do not depend on the ocular geometry; hence, it is possible to compare the ocular profiles belonging to the same subject (right and left eye) as well as to different populations. In this paper, the developed procedure is applied on two subjects’ eyes: a healthy case and another affected by an ocular malignant lesion. However, the method has already been tested on a bigger group of subjects for clinical purpose. For demonstrating the potentiality of this method, both intra- and inter-examiner repeatability were investigated in terms of coefficients of repeatability (COR). All OST indices showed repeatability with small intra-examiner (%COR 0.06–0.80) and inter-examiner variability (%COR 0.03–0.94). Measured OSTs and thermal maps clearly showed the clinical condition of the eyes investigated. The subject with no ocular pathology had no significant difference (P value = 0.25) between the OSTs of the right and left eye. On the contrary, the eye affected by a malignant lesion was significantly warmer (P value < 0.0001) than the contralateral, where the lesion was located. This new procedure demonstrated its reliability; it is featured by simplicity, immediacy, modularity, and genericity. The latter point is extremely precious as thermography has been used, in the last decades, in different clinical applications.

Ocular thermography and normalization process

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Purslow C, Wolffsohn JS (2005) Ocular surface temperature: a review. Eye Contact Lens 31(3):117–123

    Article  Google Scholar 

  2. Tan JH, Ng EYK, Acharya UR, Chee C (2009) Infrared thermography on ocular surface temperature: a review. Infrared Phys Technol 52(4):97–108

    Article  CAS  Google Scholar 

  3. Faust O, Acharya UR, Ng EYK, Tan JH, Yu W (2014) Application of infrared thermography in computer aided diagnosis. Infrared Phys Technol 66:160–175

    Article  Google Scholar 

  4. Mapstone R (1968) Measurement of corneal temperature. Exp Eye Res 7:237–243

    Article  CAS  Google Scholar 

  5. Morgan PB, Soh MP, Efron N, Tullo AB (1993) Potential applications of ocular thermography. Optom Vis Sci 70(7):568–576

    Article  CAS  Google Scholar 

  6. Efron N, Young G, Brennan NA (1989) Ocular surface temperature. Curr Eye Res 8(9):901–906

    CAS  PubMed  Google Scholar 

  7. Fujishima H, Toda I, Yamada M, Sato N, Tsubota K (1996) Corneal temperature in patients with dry eye evaluated by infrared radiation thermometry. Br J Ophthalmol 80(1):29–32

    Article  CAS  Google Scholar 

  8. Mori A, Oguchi Y, Okusawa Y, Ono M, Fujishima H, Tsubota K (1997) Use of high-speed, high-resolution thermography to evaluate the tear film layer. Am J Ophthalmol 124(6):729–735

    Article  CAS  Google Scholar 

  9. Sodi A, Giambene B, Falaschi G, Caputo R, Innocenti B, Corvi A, Menchini U (2007) Ocular surface temperature in central retinal vein occlusion: preliminary data. Eur J Ophthalmol 17(5):755–759

    Article  CAS  Google Scholar 

  10. Sodi A, Giambene B, Miranda P, Falaschi G, Corvi A, Menchini U (2009) Ocular surface temperature in diabetic retinopathy: a pilot study by infrared thermography. Eur J Ophthalmol 19(6):1004–1008

    Article  Google Scholar 

  11. Martin D, Fatt I (1986) The presence of a contact lens induces a very small increase in the anterior corneal surface temperature. Acta Ophthalmol 64(5):512–518

    Article  CAS  Google Scholar 

  12. Betney S, Morgan PB, Doyle SJ, Efron N (1997) Corneal temperature changes during photorefractive keratectomy. Cornea 16(2):158-61

    Article  Google Scholar 

  13. Corvi A, Innocenti B, Mencucci R (2006) Thermography used for analysis and comparison of different cataract surgery procedures based on phacoemulsification. Physiol Meas 27(4):371–384

    Article  Google Scholar 

  14. Galassi F, Giambene B, Corvi A, Falaschi G, Menchini U (2008) Retrobulbar hemodynamics and corneal surface temperature in glaucoma surgery. Int Ophthalmol 28(6):399–405

    Article  Google Scholar 

  15. Galassi F, Giambene B, Corvi A, Falaschi G (2007) Evaluation of ocular surface temperature and retrobulbar haemodynamics by infrared thermography and colour Doppler imaging in patients with glaucoma. Br J Ophthalmol 91(7):878–881

    Article  Google Scholar 

  16. Sodi A, Matteoli S, Giacomelli G, Finocchio L, Corvi A, Menchini U (2014) Ocular surface temperature in age-related macular degeneration. J Ophthalmol 2014:1–6. https://doi.org/10.1155/2014/281010

    Article  Google Scholar 

  17. Vannetti F, Matteoli S, Finocchio L, Lacarbonara F, Sodi A, Menchini U, Corvi A (2014) Relationship between ocular surface temperature and peripheral vasoconstriction in healthy subjects: a thermographic study. Proc Inst Mech Eng H 228(3):297–302

    Article  Google Scholar 

  18. Mencucci R, Mazzotta C, Corvi A, Terracciano L, Rechichi M, Matteoli S (2015) In vivo thermographic analysis of the corneal surface in keratoconic patients undergoing riboflavin-UV-A accelerated cross-linking. Cornea 34(3):323–327

    Article  Google Scholar 

  19. Matteoli S, Finocchio L, Biagini I, Giacomelli G, Sodi A, Corvi A, Virgili G, Rizzo S (2016) A thermographic study on eyes affected by age-related macular degeneration: comparison among various forms of the pathology and analysis of risk factors. Infrared Phys Technol 76:402–407

    Article  Google Scholar 

  20. Tan LL, Sanjay S, Morgan PB (2016) Static and dynamic measurement of ocular surface temperature in dry eyes. J Ophthalmol 2016:1–11. https://doi.org/10.1155/2016/7285132

    Article  Google Scholar 

  21. Morgan PB, Soh MP, Efron N (1999) Corneal surface temperature decreases with age. Cont Lens Anterior Eye 22(4):11–13

    Article  CAS  Google Scholar 

  22. Cardona G, Morgan PB, Efron N, Tullo AB (1996) Ocular and skin temperature in ophthalmic postherpetic neuralgia. The Pain Clinic 9(2):145–150

    Google Scholar 

  23. Craig JP, Singh I, Tomlinson A, Morgan PB, Efron N (2000) The role of tear physiology in ocular surface temperature. Eye (Lond) 14(Pt 4):635–641

    Article  Google Scholar 

  24. Purslow C, Wolffsohn JS, Santodomingo-Rubido J (2005) The effect of contact lens wear on dynamic ocular surface temperature. Cont Lens Anterior Eye. 28(1):29–36

    Article  Google Scholar 

  25. Purslow C, Wolffsohn J (2007) The relation between physical properties of the anterior eye and ocular surface temperature. Optom Vis Sci 84(3):197–201

    Article  Google Scholar 

  26. Chang TC, Hsiao YL, Liao SL (2008) Application of digital infrared thermal imaging in determining inflammatory state and follow-up effect of methylprednisolone pulse therapy in patients with Graves’ ophthalmopathy. Graefes Arch Clin Exp Ophthalmol 246:45

    Article  Google Scholar 

  27. Kamao T, Yamaguchi M, Kawasaki S, Mizoue S, Shiraishi A, Ohashi Y (2011) Screening for dry eye with newly developed ocular surface thermographer. Am J Ophthalmol 151(5):782–791

    Article  Google Scholar 

  28. Su TY, Hwa CK, Liu PH, Wu MH, Chang DO, Su PF, Chang SW, Chiang HK (2011) Noncontact detection of dry eye using a custom designed infrared thermal image system. J Biomed Opt 16(4):046009

    Article  Google Scholar 

  29. Tan JH, Ng EYK, Acharya UR (2010) Evaluation of tear evaporation from ocular surface by functional infrared thermography. Med Phys 37(11):6022–6034

    Article  Google Scholar 

  30. Acharya UR, Tan JH, Vidya S, Yeo S, Too CL, Lim WJE, Chua CK, Tong L (2014) Diagnosis of response and non-response to dry eye treatment using infrared thermography images. Infrared Phys Technol 67:497–503

    Article  Google Scholar 

  31. Acharya UR, Tan JH, Koh JEW, Sudarshan VK, Yeo S, Too CL, Chua CK, Ng EYK, Tong L (2015) Automated diagnosis of dry eye using infrared thermography images. Infrared Phys Technol 71:263–271

    Article  Google Scholar 

  32. Matteoli S, Favuzza E, Mazzantini L, Aragona P, Cappelli S, Corvi A, Mencucci R (2017) Ocular surface temperature in patients with evaporative and aqueous-deficient dry eyes: a thermographic approach. Physiol Meas 38(8):1503–1512

    Article  CAS  Google Scholar 

  33. Tan LL, Sanjay S, Morgan PB (2016) Repeatability of infrared ocular thermography in assessing healthy and dry eyes. Cont Lens Anterior Eye 39(4):284–292

    Article  Google Scholar 

  34. Tan L, Cai ZQ, Lai NS (2009) Accuracy and sensitivity of the dynamic ocular thermography and inter-subjects ocular surface temperature (OST) in Chinese young adults. Cont Lens Anterior Eye. 32(2):78–83

    Article  Google Scholar 

  35. Acharya UR, Ng EY, Yee GC, Hua TJ, Kagathi M (2009) Analysis of normal human eye with different age groups using infrared images. J Med Syst 33(3):207–213

    Article  Google Scholar 

  36. Morgan PB, Tullo AB, Efron N (1995) Infrared thermography of the tear film in dry eye. Eye 9:615–618

    Article  Google Scholar 

  37. Murphy PJ, Morgan PB, Patel S, Marshall J (1999) Corneal surface temperature change as the mode of stimulation of the non-contact corneal aesthesiometer. Cornea 18(3):333–342

    Article  CAS  Google Scholar 

  38. Chiang HK, Chen CY, Cheng HY, Chen KH, Chang DO (2006) Development of infrared thermal imager for dry eye diagnosis. Infrared and Photoelectr Imagers and Detector Devices II 6294:629406–629408

    Article  Google Scholar 

  39. Tan JH, Ng EYK, Acharya UR, Chee C (2010) Study of normal ocular thermogram using textural parameters. Infrared Phys Technol 53(2):120–126

    Article  Google Scholar 

  40. Tan JH, Ng EYK, Acharya UR, Chee C (2010) Automated study of ocular thermal images: comprehensive analysis of corneal health with different age group subjects and validation. Digit Signal Process 20(6):1579–1591

    Article  Google Scholar 

  41. Tan JH, Ng EYK, Acharya UR (2011) Evaluation of topographical variation in ocular surface temperature by functional infrared thermography. Infrared Phys Technol 54(6):469–477

    Article  Google Scholar 

  42. Tan JH, Ng EY, Acharya UR (2011) An efficient automated algorithm to detect ocular surface temperature on sequence of thermograms using snake and target tracing function. J Med Syst 35(5):949–958

    Article  Google Scholar 

  43. Morgan PB, Ocular thermography in health and disease, PhD Thesis University of Manchester, 1994

  44. Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1(8476):307–310

    Article  CAS  Google Scholar 

  45. Bland JM, Altman DG (1996) Statistical notes: measurement error. BMJ 312:1654

    Article  CAS  Google Scholar 

  46. Owen R, Ramlakhan S, Saatchi R, Burke D (2017) Development of a high-resolution infrared thermographic imaging method as a diagnostic tool for acute undifferentiated limp in young children. Med Biol Eng Comput. https://doi.org/10.1007/s11517-017-1749-0

    Article  Google Scholar 

  47. Wahab AA, Salim MIM, Ahamat MA, Manaf NA, Yunus J, Lai KW (2016) Thermal distribution analysis of three-dimensional tumor-embedded breast models with different breast density compositions. Med Biol Eng Comput 54:1363–1373

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, University of Florence, via di S. Marta 3, 50139, Florence, Italy

    Sara Matteoli, Davide Coppini & Andrea Corvi

Authors
  1. Sara Matteoli
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Davide Coppini
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Andrea Corvi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sara Matteoli.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

Not required

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Matteoli, S., Coppini, D. & Corvi, A. A novel image processing procedure for thermographic image analysis. Med Biol Eng Comput 56, 1747–1756 (2018). https://doi.org/10.1007/s11517-018-1800-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11517-018-1800-9

Keywords

Search

Navigation