A computer-aided tracking and motion analysis with ultrasound (CAT & MAUS) system for the description of hip joint kinematics

Abstract

Purpose: Investigation of joint kinematics contributes to developing a better understanding of musculoskeletal conditions. However, the most commonly used optoelectronic motion analysis systems cannot determine the movements of underlying bone landmarks with high accuracy because of soft tissue artefacts. The aim of this paper was to present a computer-aided measurement system to track the underlying bone anatomy in a 3D global coordinate frame and describe hip joint kinematics of ten healthy volunteers during gait.

Methods: We have developed a measurement tool with an image-based computer-aided post-processing pipeline for automatic bone segmentation in ultrasound (US) images and a globally optimal 3D surface-to-surface registration method to quantify hip joint movements. The segmentation algorithm exploits US intensity profiles, including information about the integrated backscattering, acoustic shadows, and local phase features. A global optimization method is applied based on the traditional iterative closest point registration algorithm, which is robust to initialization. The International Society of Biomechanics recommended joint kinematics descriptor has been adapted to calculate the joint kinematics.

Results: The developed system prototype has been validated with a ball-joint femoral phantom and tested in vivo with 10 volunteers. The maximum Euclidean distance error of the automatic bone segmentation is less than 2 pixels (approximately 0.2 mm). The maximum absolute rotation angle error is less than [Formula: see text].

Conclusion: This computer-aided tracking and motion analysis with ultrasound (CAT & MAUS) system shows the feasibility of describing hip joint kinematics for clinical investigation and diagnosis using an image-based solution.

Keywords: Bone ultrasound; Joint kinematics; Registration; Segmentation.