Modeling the human aorta for MR-driven real-time virtual endoscopy

Klaus J. Kirchberg; Andreas Wimmer; Christine H. Lorenz

Modeling the human aorta for MR-driven real-time virtual endoscopy

Klaus J. Kirchberg, Andreas Wimmer, Christine H. Lorenz

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

Abstract

As interventional magnetic resonance imaging (iMRI) is getting closer to clinical practice, new means of visualization and navigation are required. We present an approach to create a virtual endoscopic view inside the human aorta in real-time. In our approach, defined crosssectional slices are acquired and segmented in a highly optimized fashion. A geometric shape model is fit to the segmentation points and continuously updated during the intervention. The physician can then view and navigate inside the structure to plan the intervention and get immediate feedback about the procedure. As a component of this system, this work focuses on the segmentation of the cross-sectional images and the fitting of the shape model. We present a real-time 2D segmentation implementation for this application domain and a model fitting scheme for a generalized cylinder (GC) model. For the latter we employ a new scheme for choosing the local reference frame.

Original language	English (US)
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publisher	Springer Verlag
Pages	470-477
Number of pages	8
Volume	4190 LNCS - I
ISBN (Print)	3540447075, 9783540447078
State	Published - 2006
Externally published	Yes
Event	9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 - Copenhagen, Denmark Duration: Oct 1 2006 → Oct 6 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4190 LNCS - I
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Other

Other	9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006
Country/Territory	Denmark
City	Copenhagen
Period	10/1/06 → 10/6/06

ASJC Scopus subject areas

General Computer Science
Theoretical Computer Science

Cite this

Kirchberg, K. J., Wimmer, A., & Lorenz, C. H. (2006). Modeling the human aorta for MR-driven real-time virtual endoscopy. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4190 LNCS - I, pp. 470-477). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4190 LNCS - I). Springer Verlag.

Modeling the human aorta for MR-driven real-time virtual endoscopy. / Kirchberg, Klaus J.; Wimmer, Andreas; Lorenz, Christine H.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4190 LNCS - I Springer Verlag, 2006. p. 470-477 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4190 LNCS - I).

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

Kirchberg, KJ, Wimmer, A & Lorenz, CH 2006, Modeling the human aorta for MR-driven real-time virtual endoscopy. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4190 LNCS - I, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4190 LNCS - I, Springer Verlag, pp. 470-477, 9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006, Copenhagen, Denmark, 10/1/06.

Kirchberg KJ, Wimmer A, Lorenz CH. Modeling the human aorta for MR-driven real-time virtual endoscopy. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4190 LNCS - I. Springer Verlag. 2006. p. 470-477. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

Kirchberg, Klaus J. ; Wimmer, Andreas ; Lorenz, Christine H. / Modeling the human aorta for MR-driven real-time virtual endoscopy. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4190 LNCS - I Springer Verlag, 2006. pp. 470-477 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{d20d254bcd634b61a9f7b1d5b65a9be3,

title = "Modeling the human aorta for MR-driven real-time virtual endoscopy",

abstract = "As interventional magnetic resonance imaging (iMRI) is getting closer to clinical practice, new means of visualization and navigation are required. We present an approach to create a virtual endoscopic view inside the human aorta in real-time. In our approach, defined crosssectional slices are acquired and segmented in a highly optimized fashion. A geometric shape model is fit to the segmentation points and continuously updated during the intervention. The physician can then view and navigate inside the structure to plan the intervention and get immediate feedback about the procedure. As a component of this system, this work focuses on the segmentation of the cross-sectional images and the fitting of the shape model. We present a real-time 2D segmentation implementation for this application domain and a model fitting scheme for a generalized cylinder (GC) model. For the latter we employ a new scheme for choosing the local reference frame.",

author = "Kirchberg, {Klaus J.} and Andreas Wimmer and Lorenz, {Christine H.}",

year = "2006",

language = "English (US)",

isbn = "3540447075",

volume = "4190 LNCS - I",

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

publisher = "Springer Verlag",

pages = "470--477",

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

note = "9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006 ; Conference date: 01-10-2006 Through 06-10-2006",

}

TY - GEN

T1 - Modeling the human aorta for MR-driven real-time virtual endoscopy

AU - Kirchberg, Klaus J.

AU - Wimmer, Andreas

AU - Lorenz, Christine H.

PY - 2006

Y1 - 2006

N2 - As interventional magnetic resonance imaging (iMRI) is getting closer to clinical practice, new means of visualization and navigation are required. We present an approach to create a virtual endoscopic view inside the human aorta in real-time. In our approach, defined crosssectional slices are acquired and segmented in a highly optimized fashion. A geometric shape model is fit to the segmentation points and continuously updated during the intervention. The physician can then view and navigate inside the structure to plan the intervention and get immediate feedback about the procedure. As a component of this system, this work focuses on the segmentation of the cross-sectional images and the fitting of the shape model. We present a real-time 2D segmentation implementation for this application domain and a model fitting scheme for a generalized cylinder (GC) model. For the latter we employ a new scheme for choosing the local reference frame.

AB - As interventional magnetic resonance imaging (iMRI) is getting closer to clinical practice, new means of visualization and navigation are required. We present an approach to create a virtual endoscopic view inside the human aorta in real-time. In our approach, defined crosssectional slices are acquired and segmented in a highly optimized fashion. A geometric shape model is fit to the segmentation points and continuously updated during the intervention. The physician can then view and navigate inside the structure to plan the intervention and get immediate feedback about the procedure. As a component of this system, this work focuses on the segmentation of the cross-sectional images and the fitting of the shape model. We present a real-time 2D segmentation implementation for this application domain and a model fitting scheme for a generalized cylinder (GC) model. For the latter we employ a new scheme for choosing the local reference frame.

UR - http://www.scopus.com/inward/record.url?scp=33750276440&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33750276440&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:33750276440

SN - 3540447075

SN - 9783540447078

VL - 4190 LNCS - I

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

SP - 470

EP - 477

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

PB - Springer Verlag

T2 - 9th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2006

Y2 - 1 October 2006 through 6 October 2006

ER -

Modeling the human aorta for MR-driven real-time virtual endoscopy

Abstract

Publication series

Other

ASJC Scopus subject areas

Other files and links

Fingerprint

Cite this