Thermographic Computational Analyses of a 3D Model of a Scanned Breast

  • Alisson Augusto Azevedo Figueiredo
  • Gabriela Lima Menegaz
  • Henrique Coelho Fernandes
  • Gilmar Guimaraes
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11071)


Breast cancer is the most common type of cancer among women. Cancer cells are characterized by having a higher metabolic activity and superior vascularization when compared to healthy cells. The internal heat generated by tumors travels to the skin surface where an infrared camera is capable of detecting small temperatures variations on the dermal surface. Breast cancer diagnosis using only thermal images is still not accepted by the medical community which makes necessary another exam to confirm the disease. This work presents a methodology which allows identification of breast cancer using only simulated thermal images. Experiments are performed in a three-dimensional breast geometry obtained with a 3D digital scanning. The procedure starts with the 3D scanning of a model of a real female breast using a “Picza LPX-600RE 3D Laser Scanner” to generate the breast virtual geometry. This virtual 3D model is then used to simulate the heat transfer phenomena using Finite Element Model (FEM). The simulated thermal images of the breast surface are obtained via the FEM model. Based on the temperature difference of a healthy breast and a breast with cancer it is possible to identify the presence of a tumor by analyzing the biggest thermal amplitudes. Results obtained with the FEM model indicate that it is possible to identify breast cancer using only infrared images.


Breast cancer 3D scanning Thermal images Numerical simulation Inverse problem 



The authors would like to gratefully acknowledge the support of the following Brazilian agencies: FAPEMIG, Minas Gerais Research Funding Foundation; CNPq, National Council for Scientific and Technological Development; and CAPES, Coordination for the Improvement of Higher Education Personnel.


  1. 1.
    Agnelli, J.P., Barrea, A., Turner, C.V.: Tumor location and parameter estimation by thermography. Math. Comput. Model. 53(7–8), 1527–1534 (2011)CrossRefGoogle Scholar
  2. 2.
    Amri, A., Pulko, S.H., Wilkinson, A.J.: Potentialities of steady-state and transient thermography in breast tumour depth detection: a numerical study. Comput. Methods Programs Biomed. 123, 68–80 (2016)CrossRefGoogle Scholar
  3. 3.
    Bhowmik, A., Repaka, R.: Estimation of growth features and thermophysical properties of melanoma within 3-D human skin using genetic algorithm and simulated annealing. Int. J. Heat Mass Transf. 98, 81–95 (2016)CrossRefGoogle Scholar
  4. 4.
    Byer, C.O., Galliano, G., Shriver, S.P.: Dimensions of Human Sexuality. McGraw-Hill Humanities Social, New York (2002)Google Scholar
  5. 5.
    Chato, J.: Heat transfer to blood vessels. J. Biomech. Eng. 102(2), 110–118 (1980)CrossRefGoogle Scholar
  6. 6.
    Gautherie, M.: Thermopathology of breast cancer: measurement and analysis of in vivo temperature and blood flow. Ann. New York Acad. Sci. 335(1), 383–415 (1980)CrossRefGoogle Scholar
  7. 7.
    Gourd, E.: Breast thermography alone no substitute for mammography. Lancet Oncol. 19(2), E78–E78 (2018)CrossRefGoogle Scholar
  8. 8.
    Han, F., Liang, C., Shi, G., Wang, L., Li, K.: Clinical applications of internal heat source analysis for breast cancer identification. Gent. Mol. Res. 14(1), 1450–60 (2015)CrossRefGoogle Scholar
  9. 9.
    Hossain, S., Mohammadi, F.A.: Tumor parameter estimation considering the body geometry by thermography. Comput. Biol. Med. 76, 80–93 (2016)CrossRefGoogle Scholar
  10. 10.
    Ng, E.Y., Sudharsan, N.: Computer simulation in conjunction with medical thermography as an adjunct tool for early detection of breast cancer. BMC Cancer 4(1), 17 (2004)CrossRefGoogle Scholar
  11. 11.
    Pavithra, P., Ravichandran, K., Sekar, K., Manikandan, R.: The effect of thermography on breast cancer detection. Syst. Rev. Pharm. 9, 10–16 (2018)CrossRefGoogle Scholar
  12. 12.
    Pennes, H.H.: Analysis on tissue arterial blood temperature in the resting human forearm. Appl. Physiol. 1(2), 93–122 (1948)CrossRefGoogle Scholar
  13. 13.
    Shah, R., Rosso, K., Nathanson, S.D.: Pathogenesis, prevention, diagnosis and treatment of breast cancer. World J. Clin. Oncol. 5(3), 283 (2014)CrossRefGoogle Scholar
  14. 14.
    Siegel, R.L., et al.: Colorectal cancer statistics, 2017. CA Cancer J. Clin. 67(3), 177–193 (2017)CrossRefGoogle Scholar
  15. 15.
  16. 16.
    Wang, L.: Early diagnosis of breast cancer. Sensors 17(7), 1–20 (2017). Article number 1572CrossRefGoogle Scholar

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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.School of Mechanical EngineeringFederal University of UberlandiaUberlandiaBrazil
  2. 2.School of Computer ScienceFederal University of UberlandiaUberlandiaBrazil

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