The University of Southampton
University of Southampton Institutional Repository

Lumbar Spine Location in Fluoroscopic Images by Evidence Gathering

Lumbar Spine Location in Fluoroscopic Images by Evidence Gathering
Lumbar Spine Location in Fluoroscopic Images by Evidence Gathering
Low back pain (LBP) is a very common problem and lumbar segmental instability is one of the causes. It is important to investigate lumbar spine movement in order to understand instability better and as an aid to diagnosis. Digital videofluoroscopy provides a method of quantifying the motion of individual vertebrae, but due to the relatively poor image quality, it is difficult and time consuming to locate landmarks manually, from which the kinematics can be calculated. Some semi-automatic approaches have already been developed but these are still time consuming and require some manual interaction. In this paper we apply the Hough transform (HT) to locate the lumbar spinal segments automatically. The HT is a powerful tool in computer vision and it has good performance in noise and partial occlusion. A recent arbitrary shape representation avoids problems inherent with tabular representations in the generalised HT (GHT) by describing shapes using a continuous formulation. The target shape is described by a set of Fourier descriptors, which vote in an accumulator space from which the object parameters of translation (including the x and y direction), rotation and scale can be determined. At present, this algorithm has been applied to the images of lumbar spine, and has been shown to provide satisfactory results. Further work will concentrate on reducing the computational time for real-time application, and on approaches to refine information at the apices, given initialisation by the new HT method.
1-901725-11-1
45-48
Zheng, Yalin
cf121a1d-9a54-4d7c-aeea-6354fe19d880
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Allen, Robert
61929c7d-45ee-4a1d-ba45-164420621020
Arridge, Simon
d02551c9-1657-44b4-a94f-e1371ec7a233
Todd-Pokropek, Andrew
309d666b-7b34-4a79-ac94-653bc71c0099
Zheng, Yalin
cf121a1d-9a54-4d7c-aeea-6354fe19d880
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Allen, Robert
61929c7d-45ee-4a1d-ba45-164420621020
Arridge, Simon
d02551c9-1657-44b4-a94f-e1371ec7a233
Todd-Pokropek, Andrew
309d666b-7b34-4a79-ac94-653bc71c0099

Zheng, Yalin, Nixon, Mark S. and Allen, Robert (2000) Lumbar Spine Location in Fluoroscopic Images by Evidence Gathering. Arridge, Simon and Todd-Pokropek, Andrew (eds.) Proceedings of Medical Image Understanding and Analysis MIUA2000. pp. 45-48 .

Record type: Conference or Workshop Item (Other)

Abstract

Low back pain (LBP) is a very common problem and lumbar segmental instability is one of the causes. It is important to investigate lumbar spine movement in order to understand instability better and as an aid to diagnosis. Digital videofluoroscopy provides a method of quantifying the motion of individual vertebrae, but due to the relatively poor image quality, it is difficult and time consuming to locate landmarks manually, from which the kinematics can be calculated. Some semi-automatic approaches have already been developed but these are still time consuming and require some manual interaction. In this paper we apply the Hough transform (HT) to locate the lumbar spinal segments automatically. The HT is a powerful tool in computer vision and it has good performance in noise and partial occlusion. A recent arbitrary shape representation avoids problems inherent with tabular representations in the generalised HT (GHT) by describing shapes using a continuous formulation. The target shape is described by a set of Fourier descriptors, which vote in an accumulator space from which the object parameters of translation (including the x and y direction), rotation and scale can be determined. At present, this algorithm has been applied to the images of lumbar spine, and has been shown to provide satisfactory results. Further work will concentrate on reducing the computational time for real-time application, and on approaches to refine information at the apices, given initialisation by the new HT method.

Text
miua2000.pdf - Other
Download (316kB)

More information

Published date: July 2000
Additional Information: Organisation: BMVA, BIR, RCR, IEE, IPEM, RAE Address: University of College London
Venue - Dates: Proceedings of Medical Image Understanding and Analysis MIUA2000, 2000-06-30
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 255986
URI: http://eprints.soton.ac.uk/id/eprint/255986
ISBN: 1-901725-11-1
PURE UUID: 5564e2dc-1ff5-4638-ad96-b4eef0ff66a1
ORCID for Mark S. Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 17 Jul 2001
Last modified: 07 Oct 2020 02:32

Export record

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.

×