Automatic identification of radius and ulna bone landmarks on 3D virtual models

Derek F.R. van Loon*, Eline M. van Es, Denise Eygendaal, H.E.J. Veeger, Joost W. Colaris

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Background: For bone morphology and biomechanics analysis, landmarks are essential to define position, orientation, and shape. These landmarks define bone and joint coordinate systems and are widely used in these research fields. Currently, no method is known for automatically identifying landmarks on virtual 3D bone models of the radius and ulna. This paper proposes a knowledge-based method for locating landmarks and calculating a coordinate system for the radius, ulna, and combined forearm bones, which is essential for measuring forearm function. This method does not rely on pre-labeled data. Validation: The algorithm is validated by comparing the landmarks placed by the algorithm with the mean position of landmarks placed by a group of experts on cadaveric specimens regarding distance and orientation. Results: The median Euclidean distance differences between all the automated and reference landmarks range from 0.4 to 1.8 millimeters. The median angular differences of the coordinate system of the radius and ulna range from -1.4 to 0.6 degrees. The forearm coordinate system's median errors range from -0.2 to 2.0 degrees. The median error in calculating the rotational position of the radius relative to the ulna is 1.8 degrees. Conclusion: The automatic method's applicability depends on the use context and desired accuracy. However, the current method is a validated first step in the automatic analysis of the three-dimensional forearm anatomy.

Original languageEnglish
Article number108891
Number of pages9
JournalComputers in Biology and Medicine
Volume179
DOIs
Publication statusPublished - 2024

Keywords

  • Automatic method
  • Computer-assisted orthopedic surgery (CAOS)
  • Forearm landmark detection
  • Knowledge-based

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