The University of Southampton
University of Southampton Institutional Repository

Lumbar spine visualisation based upon kinematic analysis from videofluoroscopic imaging

Lumbar spine visualisation based upon kinematic analysis from videofluoroscopic imaging
Lumbar spine visualisation based upon kinematic analysis from videofluoroscopic imaging
Low back pain is a significant problem and its cost is enormous to society. However, diagnosis of the underlying causes remains problematic despite extensive study. Reasons for this arise from the deep-rooted situation of the spine and also from its structural complexity. Clinicians have to mentally convert 2-D image information into a 3-D form to gain a better understanding of structural integrity. Therefore, visualisation and animation may be helpful for understanding, diagnosis and for guiding therapy. Some low back pain originates from mechanical disorders, and study of the spine kinematics may provide an insight into the source of the problem. Digital videofluoroscopy was used in this study to provide 2-D image sequences of the spine in motion, but the images often suffer due to noise, exacerbated by the very low radiation dosage. Thus determining vertebrae position within the image sequence presents a considerable challenge. This paper describes a combination of spine kinematic measurements with a solid model of the human lumbar spine for visualisation of spine motion. Since determination of the spine kinematics provides the foundation and vertebral extraction is at the core, this is discussed in detail. Edge detection is a key feature of segmentation and it is shown that phase congruency performs better than most established methods with the rather low-grade image sequences from fluoroscopy. The Hough transform is then applied to determine the positions of vertebrae in each frame of a motion sequence. In the Hough transform, Fourier descriptors are used to represent the vertebral shapes. The results show that the Hough transform is a very promising technique for vertebral extraction from videofluoroscopic images. A dynamic visualisation package has been developed in order to view the moving lumbar spine from any angle and viewpoint. Wire frame models of the vertebrae were built by using CT images from the Visible Human Project and these models are scaled to match the fluoroscopic image data. For animation, the spinal kinematic data from the motion study is incorporated.
Low back pain, Visualisation and animation, Digital videofluoroscopy, Phase congruency, Hough transform
1350-4533
171-179
Zheng, Yalin
cf121a1d-9a54-4d7c-aeea-6354fe19d880
Allen, Robert
956a918f-278c-48ef-8e19-65aa463f199a
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Zheng, Yalin
cf121a1d-9a54-4d7c-aeea-6354fe19d880
Allen, Robert
956a918f-278c-48ef-8e19-65aa463f199a
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12

Zheng, Yalin, Allen, Robert and Nixon, Mark S. (2003) Lumbar spine visualisation based upon kinematic analysis from videofluoroscopic imaging. Medical Engineering & Physics, 25 (3), 171-179. (doi:10.1016/S1350-4533(02)00182-0).

Record type: Article

Abstract

Low back pain is a significant problem and its cost is enormous to society. However, diagnosis of the underlying causes remains problematic despite extensive study. Reasons for this arise from the deep-rooted situation of the spine and also from its structural complexity. Clinicians have to mentally convert 2-D image information into a 3-D form to gain a better understanding of structural integrity. Therefore, visualisation and animation may be helpful for understanding, diagnosis and for guiding therapy. Some low back pain originates from mechanical disorders, and study of the spine kinematics may provide an insight into the source of the problem. Digital videofluoroscopy was used in this study to provide 2-D image sequences of the spine in motion, but the images often suffer due to noise, exacerbated by the very low radiation dosage. Thus determining vertebrae position within the image sequence presents a considerable challenge. This paper describes a combination of spine kinematic measurements with a solid model of the human lumbar spine for visualisation of spine motion. Since determination of the spine kinematics provides the foundation and vertebral extraction is at the core, this is discussed in detail. Edge detection is a key feature of segmentation and it is shown that phase congruency performs better than most established methods with the rather low-grade image sequences from fluoroscopy. The Hough transform is then applied to determine the positions of vertebrae in each frame of a motion sequence. In the Hough transform, Fourier descriptors are used to represent the vertebral shapes. The results show that the Hough transform is a very promising technique for vertebral extraction from videofluoroscopic images. A dynamic visualisation package has been developed in order to view the moving lumbar spine from any angle and viewpoint. Wire frame models of the vertebrae were built by using CT images from the Visible Human Project and these models are scaled to match the fluoroscopic image data. For animation, the spinal kinematic data from the motion study is incorporated.

Full text not available from this repository.

More information

Published date: April 2003
Keywords: Low back pain, Visualisation and animation, Digital videofluoroscopy, Phase congruency, Hough transform
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 257866
URI: http://eprints.soton.ac.uk/id/eprint/257866
ISSN: 1350-4533
PURE UUID: c85725e9-782b-4e21-aeb4-bf891442d264
ORCID for Mark S. Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 20 Nov 2003
Last modified: 10 Dec 2019 01:59

Export record

Altmetrics

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×