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Image Processing as an Auxiliary Methodology for Analysis of Thermograms

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XXVII Brazilian Congress on Biomedical Engineering (CBEB 2020)

Part of the book series: IFMBE Proceedings ((IFMBE,volume 83))

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Abstract

This paper presents a study by image processing to automate the thermogram analysis method of patients diagnosed with cancer. The objective is to develop a semiautomatic segmentation model of thermographic images using the Python computational language. A segmentation routine is proposed based on a region growth algorithm capable of grouping similar pixels to a Thermogram Region of Interest (ROI), starting from the manual positioning of the seed pixel, which is why the test is said to be semiautomatic. The tests were performed on twenty thermograms collected from patients with breast and thyroid cancer. As results it was verified that the proposed model comprises the tumor region with greater reliability than the manual delimitation method, thus the average and the minimum temperatures are higher (compared to the manual method) as it ensures that temperature points outside the real nodular range are not included in the ROI. As for operating time, the proposed method performs the ROI delimitation faster than the manual method. For future work, we suggest the statistical study for nodule benignity or malignancy based on thermal difference recorded in the ROI thermograms analyzed with the semiautomatic segmentation.

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Acknowledgements

For sharing information, we thank researchers José Ramón González (UFF) and Adriano dos Passos (UFPR).

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES, Coordination for the Improvement of Higher Education Personnel)—Brazil—Finance Code 001.

Conflict of Interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. Programa de Pós-Graduação em Engenharia Biomédica, Universidade Tecnológica Federal do Paraná (UTFPR), Sete de Setembro, Curitiba, 3165, Brazil

    C. A. Schadeck, F. Ganacim, L. Ulbricht & Cezar Schadeck

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  1. C. A. Schadeck
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  2. F. Ganacim
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  3. L. Ulbricht
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  4. Cezar Schadeck
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, Universidade Federal do Espírito Santo, Vitória, Brazil

    Teodiano Freire Bastos-Filho

  2. Department of Electrical Engineering, Universidade Federal do Espírito Santo, Vitória, Brazil

    Eliete Maria de Oliveira Caldeira

  3. Department of Electrical Engineering, Universidade Federal do Espírito Santo, Vitória, Brazil

    Anselmo Frizera-Neto

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Schadeck, C.A., Ganacim, F., Ulbricht, L., Schadeck, C. (2022). Image Processing as an Auxiliary Methodology for Analysis of Thermograms. In: Bastos-Filho, T.F., de Oliveira Caldeira, E.M., Frizera-Neto, A. (eds) XXVII Brazilian Congress on Biomedical Engineering. CBEB 2020. IFMBE Proceedings, vol 83. Springer, Cham. https://doi.org/10.1007/978-3-030-70601-2_228

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  • DOI: https://doi.org/10.1007/978-3-030-70601-2_228

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-70600-5

  • Online ISBN: 978-3-030-70601-2

  • eBook Packages: EngineeringEngineering (R0)

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