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

Ofri Sadowsky; Gouthami Chintalapani; Russell H. Taylor

doi:10.1007/978-3-540-75759-7_63

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

Ofri Sadowsky, Gouthami Chintalapani, Russell H. Taylor

Whiting School of Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

49 Scopus citations

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 language	English (US)
Title of host publication	Medical Image Computing and Computer-Assisted Intervention - MICCAI 2007 - 10th International Conference, Proceedings
Publisher	Springer Verlag
Pages	519-526
Number of pages	8
Edition	PART 2
ISBN (Print)	9783540757580
DOIs	https://doi.org/10.1007/978-3-540-75759-7_63
State	Published - 2007
Event	10th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2007 - Brisbane, Australia Duration: Oct 29 2007 → Nov 2 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	4792 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	10th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2007
Country/Territory	Australia
City	Brisbane
Period	10/29/07 → 11/2/07

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-540-75759-7_63

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 2007 - 10th International Conference, Proceedings (PART 2 ed., pp. 519-526). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4792 LNCS, No. PART 2). Springer Verlag. https://doi.org/10.1007/978-3-540-75759-7_63

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 2007 - 10th International Conference, Proceedings. PART 2. ed. Springer Verlag, 2007. p. 519-526 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4792 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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 2007 - 10th International Conference, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 4792 LNCS, Springer Verlag, pp. 519-526, 10th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2007, Brisbane, Australia, 10/29/07. https://doi.org/10.1007/978-3-540-75759-7_63

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 2007 - 10th International Conference, Proceedings. PART 2 ed. Springer Verlag. 2007. p. 519-526. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-540-75759-7_63

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 2007 - 10th International Conference, Proceedings. PART 2. ed. Springer Verlag, 2007. pp. 519-526 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

@inproceedings{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.}",

note = "Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 10th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2007 ; Conference date: 29-10-2007 Through 02-11-2007",

year = "2007",

doi = "10.1007/978-3-540-75759-7_63",

language = "English (US)",

isbn = "9783540757580",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

number = "PART 2",

pages = "519--526",

booktitle = "Medical Image Computing and Computer-Assisted Intervention - MICCAI 2007 - 10th International Conference, Proceedings",

edition = "PART 2",

}

TY - GEN

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

U2 - 10.1007/978-3-540-75759-7_63

DO - 10.1007/978-3-540-75759-7_63

M3 - Conference contribution

C2 - 18044608

AN - SCOPUS:79551688769

SN - 9783540757580

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 519

EP - 526

BT - Medical Image Computing and Computer-Assisted Intervention - MICCAI 2007 - 10th International Conference, Proceedings

PB - Springer Verlag

T2 - 10th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2007

Y2 - 29 October 2007 through 2 November 2007

ER -

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

Abstract

Publication series

Other

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this