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Modeling the 3D Breast Surface Using Thermography

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Artificial Intelligence over Infrared Images for Medical Applications (AIIIMA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14298))

Abstract

Breast thermographies can show temperature distribution and detect abnormalities in the body on examination. This work shows an implementation allowing their used for three-dimensional (3d) models of the breast surface from their acquisition in five different angles. Firstly, breast segmentation is performed using U-Nets trained for each angle. Then, the segmented edges are transformed into parametric curves. Geometric transformation converts these curves from two-dimensional (2d) to a three-dimensional after proper rotations and translation of them. These 3D curves are described by B-splines curves and used to build a Rational Non-Uniform B-splines Surface (NURBS) for the breast region. Texture mapping is applied to project the frontal thermal data onto the 3d surface. A Likert scale-based survey was conducted with healthcare experts, and experienced academics to evaluate the final results and compare them with examples of the same persons. The results received high grades of approval and agreements.

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Acknowledgements

E.L.S.M. is supported by Federal Institute of Education, Science and Technology of Rondônia (IFRO). A.C. is supported in part by CYTED, the National Institutes of Science and Technology (INCT - MACC project), National Council for Scientific and Technological (CNPq) under grant 307638/2022-79, the Research Support Foundation of Rio de Janeiro State (FAPERJ) over CNE, SIADE-2, e-Health Rio and Digit3D (“tematico”) projects [23].

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Authors and Affiliations

  1. Department of Informatics, Federal University of Maranhão, São Luís, Brazil

    Gleidson M. Costa & Tiago B. Borchartt

  2. Federal Institute of Education, Science and Technology of Rondônia, Porto Velho, Brazil

    Eudoxia L. S. Moura

  3. Institute of Computing, Federal Fluminense University, Niterói, Brazil

    Eudoxia L. S. Moura & Aura Conci

Authors
  1. Gleidson M. Costa
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  2. Eudoxia L. S. Moura
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  3. Tiago B. Borchartt
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  4. Aura Conci
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Corresponding author

Correspondence to Gleidson M. Costa .

Editor information

Editors and Affiliations

  1. Niramai Health Analytix Pvt. Ltd., Bengaluru, India

    Siva Teja Kakileti

  2. Niramai Health Analytix Pvt. Ltd., Bengaluru, India

    Geetha Manjunath

  3. Piedmont Physical Medicine and Rehabilitation, Greenville, SC, USA

    Robert G. Schwartz

  4. University of Manchester, Manchester, UK

    Alejandro F. Frangi

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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Costa, G.M., Moura, E.L.S., Borchartt, T.B., Conci, A. (2023). Modeling the 3D Breast Surface Using Thermography. In: Kakileti, S.T., Manjunath, G., Schwartz, R.G., Frangi, A.F. (eds) Artificial Intelligence over Infrared Images for Medical Applications. AIIIMA 2023. Lecture Notes in Computer Science, vol 14298. Springer, Cham. https://doi.org/10.1007/978-3-031-44511-8_3

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  • DOI: https://doi.org/10.1007/978-3-031-44511-8_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-45657-2

  • Online ISBN: 978-3-031-44511-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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