Deformable 2D-3D registration of the pelvis with a limited field of view, using shape statistics.

Ofri Sadowsky, Gouthami Chintalapani, Russell H Taylor

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Our paper summarizes experiments for measuring the accuracy of deformable 2D-3D registration between sets of simulated x-ray images (DRR's) and a statistical shape model of the pelvis bones, which includes x-ray attenuation information ("density"). In many surgical scenarios, the images contain a truncated view of the pelvis anatomy. Our work specifically addresses this problem by examining different selections of truncated views as target images. Our atlas is derived by applying principal component analysis to a population of up to 110 instance shapes. The experiments measure the registration error with a large and truncated FOV. A typical accuracy of about 2 mm is achieved in the 2D-3D registration, compared with about 1.4 mm of an "optimal" 3D-3D registration.

Original languageEnglish (US)
Title of host publicationMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Pages519-526
Number of pages8
Volume10
EditionPt 2
StatePublished - 2007

Fingerprint

Pelvis
X-Rays
Atlases
Statistical Models
Principal Component Analysis
Anatomy
Bone and Bones
Population

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Sadowsky, O., Chintalapani, G., & Taylor, R. H. (2007). Deformable 2D-3D registration of the pelvis with a limited field of view, using shape statistics. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention (Pt 2 ed., Vol. 10, pp. 519-526)

Deformable 2D-3D registration of the pelvis with a limited field of view, using shape statistics. / Sadowsky, Ofri; Chintalapani, Gouthami; Taylor, Russell H.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 10 Pt 2. ed. 2007. p. 519-526.

Research output: Chapter in Book/Report/Conference proceedingChapter

Sadowsky, O, Chintalapani, G & Taylor, RH 2007, Deformable 2D-3D registration of the pelvis with a limited field of view, using shape statistics. in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Pt 2 edn, vol. 10, pp. 519-526.
Sadowsky O, Chintalapani G, Taylor RH. Deformable 2D-3D registration of the pelvis with a limited field of view, using shape statistics. In Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Pt 2 ed. Vol. 10. 2007. p. 519-526
Sadowsky, Ofri ; Chintalapani, Gouthami ; Taylor, Russell H. / Deformable 2D-3D registration of the pelvis with a limited field of view, using shape statistics. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 10 Pt 2. ed. 2007. pp. 519-526
@inbook{8d9b05281d9043cdae4b730aa49c4388,
title = "Deformable 2D-3D registration of the pelvis with a limited field of view, using shape statistics.",
abstract = "Our paper summarizes experiments for measuring the accuracy of deformable 2D-3D registration between sets of simulated x-ray images (DRR's) and a statistical shape model of the pelvis bones, which includes x-ray attenuation information ({"}density{"}). In many surgical scenarios, the images contain a truncated view of the pelvis anatomy. Our work specifically addresses this problem by examining different selections of truncated views as target images. Our atlas is derived by applying principal component analysis to a population of up to 110 instance shapes. The experiments measure the registration error with a large and truncated FOV. A typical accuracy of about 2 mm is achieved in the 2D-3D registration, compared with about 1.4 mm of an {"}optimal{"} 3D-3D registration.",
author = "Ofri Sadowsky and Gouthami Chintalapani and Taylor, {Russell H}",
year = "2007",
language = "English (US)",
volume = "10",
pages = "519--526",
booktitle = "Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention",
edition = "Pt 2",

}

TY - CHAP

T1 - Deformable 2D-3D registration of the pelvis with a limited field of view, using shape statistics.

AU - Sadowsky, Ofri

AU - Chintalapani, Gouthami

AU - Taylor, Russell H

PY - 2007

Y1 - 2007

N2 - Our paper summarizes experiments for measuring the accuracy of deformable 2D-3D registration between sets of simulated x-ray images (DRR's) and a statistical shape model of the pelvis bones, which includes x-ray attenuation information ("density"). In many surgical scenarios, the images contain a truncated view of the pelvis anatomy. Our work specifically addresses this problem by examining different selections of truncated views as target images. Our atlas is derived by applying principal component analysis to a population of up to 110 instance shapes. The experiments measure the registration error with a large and truncated FOV. A typical accuracy of about 2 mm is achieved in the 2D-3D registration, compared with about 1.4 mm of an "optimal" 3D-3D registration.

AB - Our paper summarizes experiments for measuring the accuracy of deformable 2D-3D registration between sets of simulated x-ray images (DRR's) and a statistical shape model of the pelvis bones, which includes x-ray attenuation information ("density"). In many surgical scenarios, the images contain a truncated view of the pelvis anatomy. Our work specifically addresses this problem by examining different selections of truncated views as target images. Our atlas is derived by applying principal component analysis to a population of up to 110 instance shapes. The experiments measure the registration error with a large and truncated FOV. A typical accuracy of about 2 mm is achieved in the 2D-3D registration, compared with about 1.4 mm of an "optimal" 3D-3D registration.

UR - http://www.scopus.com/inward/record.url?scp=79551688769&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79551688769&partnerID=8YFLogxK

M3 - Chapter

C2 - 18044608

AN - SCOPUS:79551688769

VL - 10

SP - 519

EP - 526

BT - Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention

ER -