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MICCAI Workshop on Medical Image Assisted Blomarkers' Discovery

MICCAI Workshop on Artificial Intelligence over Infrared Images for Medical Applications

MIABID 2022, AIIIMA 2022: Artificial Intelligence over Infrared Images for Medical Applications and Medical Image Assisted Biomarker Discovery pp 45–56Cite as

Thermographic Toothache Screening by Artificial Intelligence

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13602))

Abstract

Inflammatory toothache is a painful condition frequently reported by patients in the daily dental clinic, and may reach a disabling situation, directly impacting their quality of life and systemic health. Panoramic and periapical radiographies can demonstrate periapical pathologies and lesions of the dental organ, but cannot record the local sympathetic vasomotor response. Infrared thermography is a functional imaging method with no emission of ionizing radiation, it is quick to acquire, and reflects the microcirculatory dynamics of the skin surface, enlarging the vascular, nervous, and skeletal muscle, as well as inflammatory processes. The study tested the application of four models of the artificial neural network (MobileNetV2, InceptionV3, ResNet101V2, and ResNet50V2) in the detection of inflammatory toothache. The sample consisted of 76 volunteers, over 18 years old, being selected 51 volunteers with inflammatory toothache and 25 volunteers compatible with normality. They were submitted to thermographic, panoramic radiographic and clinical examinations. Among the four models tested, MobileNetV2 performed better in both front and lateral views. However, considering the ROC curve, the best performance of the automated detection of toothache cases was by the frontal image. The authors discussed how this technique can help the diagnostic accuracy in dentistry and the future perspective of artificial intelligence in the area of endodontics. Infrared thermography can provide health professionals with objective and accurate information about the vasomotor and facial neurovegetative responses in inflammatory toothache. It may assist in the screening of volunteers with inflammatory toothache using artificial neural networks.

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Author information

Authors and Affiliations

  1. Dentistry Faculty, University of São Paulo, São Paulo, Brazil

    Denise Sabbagh Haddad, Maria Aparecida Borsatti Luchetti & Emiko Saito Arita

  2. Medicine Faculty, University of São Paulo, São Paulo, Brazil

    Marcos Leal Brioschi

  3. Federal University of Technology – Paraná, Curitiba, Brazil

    Nicolas Civiero

  4. Brazilian Medical Thermology Association, São Paulo, Brazil

    Denise Sabbagh Haddad, Marcos Leal Brioschi, Nicolas Civiero & Mayco Anderson Moreira

Authors
  1. Denise Sabbagh Haddad
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  2. Marcos Leal Brioschi
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  3. Maria Aparecida Borsatti Luchetti
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  4. Nicolas Civiero
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  5. Mayco Anderson Moreira
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  6. Emiko Saito Arita
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Corresponding author

Correspondence to Marcos Leal Brioschi .

Editor information

Editors and Affiliations

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

    Siva Teja Kakileti

  2. IBM Research - Zurich, Rüschlikon, Switzerland

    Maria Gabrani

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

    Geetha Manjunath

  4. University of Haifa, Haifa, Israel

    Michal Rosen-Zvi

  5. Picture Health, Cleveland, OH, USA

    Nathaniel Braman

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

    Robert G. Schwartz

  7. University of Leeds, Leeds, UK

    Alejandro F. Frangi

  8. National Cheng Kung University, Tainan, Taiwan

    Pau-Choo Chung

  9. Cleveland Clinic, Cleveland, OH, USA

    Christopher Weight

  10. Tempus Labs, Menlo Park, CA, USA

    Vekataraman Jagadish

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Haddad, D.S., Brioschi, M.L., Luchetti, M.A.B., Civiero, N., Moreira, M.A., Arita, E.S. (2022). Thermographic Toothache Screening by Artificial Intelligence. In: Kakileti, S.T., et al. Artificial Intelligence over Infrared Images for Medical Applications and Medical Image Assisted Biomarker Discovery. MIABID AIIIMA 2022 2022. Lecture Notes in Computer Science, vol 13602. Springer, Cham. https://doi.org/10.1007/978-3-031-19660-7_5

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  • DOI: https://doi.org/10.1007/978-3-031-19660-7_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-19659-1

  • Online ISBN: 978-3-031-19660-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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