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Computational spine kinematic analysis with digitised video fluoroscopy

Computational spine kinematic analysis with digitised video fluoroscopy
Computational spine kinematic analysis with digitised video fluoroscopy

The purpose of this thesis is set to investigate spine kinematics with Digitised Video Fluoroscopy (DVF) by developing well-defined experimental protocols, easy-to-use graphical user interface software, image professing and automated tracking procedures.

Some of the developed techniques were first applied to study the spine kinematics of the subjects with vertebral fractures due to osteoporosis.  Kinematics and motion patterns of complete cycles of sagittal and lateral flexion were obtained from landmarking the DVF sequences which described segmental motions of the spine.  Compared to control subjects who did not have a fracture, fracture subjects had a more asymmetric lateral range of motion and required a longer time to complete certain phases of the motion cycle.  Five motion patterns were identified, but there was no statistical difference between the two groups in any of these patterns.  Prolonged deflection was more frequently found when the spine was moving towards the neutral position.  These suggest that segmental kinematics is useful in understanding some variances in osteoporosis subjects with vertebral fractures.  Subjects with vertebral fracture have altered spinal kinematics which could help to quantify dysfunction and response to treatment and may be an indication of instability.

Landmarking from DVF sequences forms the basis of kinematic analysis.  In order to facilitate the analysis, an automated spine motion tracking algorithm for DVF sequences using particle filters was developed.  The rotation and translation parameters were estimated from the corresponding posterior distributions. The algorithm can provide results to a precision of 1 degree in rotation estimation for the calibration sequence as well as 1-2 degrees and 1-2 pixels variability in rotation and translation estimation respectively during repeated initialisation analysis on in vivo sequences from healthy human subjects.

The developed techniques have demonstrated their reliability and usefulness in spine kinematic analysis.  They are provided as a platform for researchers to use and further develop.

University of Southampton
Lam, Shing Chun Benny
6334eb0f-23ef-45fc-8ec7-2eed49736a1f
Lam, Shing Chun Benny
6334eb0f-23ef-45fc-8ec7-2eed49736a1f

Lam, Shing Chun Benny (2007) Computational spine kinematic analysis with digitised video fluoroscopy. University of Southampton, Doctoral Thesis.

Record type: Thesis (Doctoral)

Abstract

The purpose of this thesis is set to investigate spine kinematics with Digitised Video Fluoroscopy (DVF) by developing well-defined experimental protocols, easy-to-use graphical user interface software, image professing and automated tracking procedures.

Some of the developed techniques were first applied to study the spine kinematics of the subjects with vertebral fractures due to osteoporosis.  Kinematics and motion patterns of complete cycles of sagittal and lateral flexion were obtained from landmarking the DVF sequences which described segmental motions of the spine.  Compared to control subjects who did not have a fracture, fracture subjects had a more asymmetric lateral range of motion and required a longer time to complete certain phases of the motion cycle.  Five motion patterns were identified, but there was no statistical difference between the two groups in any of these patterns.  Prolonged deflection was more frequently found when the spine was moving towards the neutral position.  These suggest that segmental kinematics is useful in understanding some variances in osteoporosis subjects with vertebral fractures.  Subjects with vertebral fracture have altered spinal kinematics which could help to quantify dysfunction and response to treatment and may be an indication of instability.

Landmarking from DVF sequences forms the basis of kinematic analysis.  In order to facilitate the analysis, an automated spine motion tracking algorithm for DVF sequences using particle filters was developed.  The rotation and translation parameters were estimated from the corresponding posterior distributions. The algorithm can provide results to a precision of 1 degree in rotation estimation for the calibration sequence as well as 1-2 degrees and 1-2 pixels variability in rotation and translation estimation respectively during repeated initialisation analysis on in vivo sequences from healthy human subjects.

The developed techniques have demonstrated their reliability and usefulness in spine kinematic analysis.  They are provided as a platform for researchers to use and further develop.

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More information

Published date: 2007

Identifiers

Local EPrints ID: 466311
URI: http://eprints.soton.ac.uk/id/eprint/466311
PURE UUID: 382f31a0-6373-4718-a640-f3dca74d8578

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Date deposited: 05 Jul 2022 05:10
Last modified: 23 Jul 2022 01:15

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Contributors

Author: Shing Chun Benny Lam

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