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

Authors :
van Loon DFR
van Es EM
Eygendaal D
Veeger DHEJ
Colaris JW
Source :
Computers in biology and medicine [Comput Biol Med] 2024 Sep; Vol. 179, pp. 108891. Date of Electronic Publication: 2024 Jul 23.
Publication Year :
2024

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.<br />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.<br />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.<br />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.<br />Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Details

Language :
English
ISSN :
1879-0534
Volume :
179
Database :
MEDLINE
Journal :
Computers in biology and medicine
Publication Type :
Academic Journal
Accession number :
39047505
Full Text :
https://doi.org/10.1016/j.compbiomed.2024.108891