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

被引：0

作者：

van Loon, Derek F.R. ^{[1
]}

van Es, Eline M. ^{[1
]}

Eygendaal, Denise ^{[1
]}

Veeger, DirkJan H.E.J. ^{[2
]}

Colaris, Joost W. ^{[1
]}

机构：

[1] Department of Orthopaedics and Sports Medicine, Erasmus MC, University Medical Center Rotterdam, Dr. Molewaterplein 40, Rotterdam

[2] Department of Biomechanical Engineering, Delft University of Technology, Mekelweg 2, Delft

来源：

Computers in Biology and Medicine | 2024年 / 179卷

关键词：

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

D O I：

10.1016/j.compbiomed.2024.108891

中图分类号：

学科分类号：

摘要：

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. © 2024 The Author(s)

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