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European Congress on Computational Methods in Applied Sciences and Engineering

ECCOMAS 2017: VipIMAGE 2017 pp 633–638Cite as

Automated Assessment of Hallux Valgus in Radiographic Images

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Part of the book series: Lecture Notes in Computational Vision and Biomechanics ((LNCVB,volume 27))

Abstract

The purpose of the study was to develop an automated method for measurement of the selected angular variables, characterizing foot skeleton based on dorsoplantar projection radiographs. The study was a retrospective analysis of radiographic data. Totally, 50 dorsoplantar projection radiographs of a weight-wearing foot were analyzed (24 left and 26 right feet) of 32 patients (23 female, 9 male). Various quantities were measured to assess the severity of hallux valgus. The measurements were performed manually and with an automated method designed in the study. The automated and manual measurements were correlated. Repeated manual measurements were additionally performed to determine the variability of manual assessment of the hallux valgus. High correlation between manual and automated measurements have been observed. The accuracy of the framework is comparable with the accuracy of manual measurements.

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Author information

Authors and Affiliations

  1. Cracow University of Technology, ul. Warszawska 24, 31-155, Krakow, Poland

    Tomasz Gąciarz & Zbisław Tabor

  2. Medical College, Jagiellonian University, ul. Kopernika 19, 31-501, Krakow, Poland

    Wadim Wojciechowski

  3. Comarch Healthcare S.A, ul. Życzkowskiego 29, 31-864, Krakow, Poland

    Wadim Wojciechowski

Authors
  1. Tomasz Gąciarz
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  2. Wadim Wojciechowski
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  3. Zbisław Tabor
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Corresponding author

Correspondence to Zbisław Tabor .

Editor information

Editors and Affiliations

  1. Universidade do Porto, Porto, Portugal

    João Manuel R.S. Tavares

  2. Universidade do Porto, Porto, Portugal

    R.M. Natal Jorge

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Gąciarz, T., Wojciechowski, W., Tabor, Z. (2018). Automated Assessment of Hallux Valgus in Radiographic Images. In: Tavares, J., Natal Jorge, R. (eds) VipIMAGE 2017. ECCOMAS 2017. Lecture Notes in Computational Vision and Biomechanics, vol 27. Springer, Cham. https://doi.org/10.1007/978-3-319-68195-5_68

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  • DOI: https://doi.org/10.1007/978-3-319-68195-5_68

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68194-8

  • Online ISBN: 978-3-319-68195-5

  • eBook Packages: EngineeringEngineering (R0)

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