Conditional shape models for cardiac motion estimation

Coert Metz; Nora Baka; Hortense Kirisli; Michiel Schaap; Theo van Walsum; Stefan Klein; Lisan Neefjes; Nico Mollet; Boudewijn Lelieveldt; Marleen de Bruijne; Wiro Niessen

doi:10.1007/978-3-642-15705-9_55

Conditional shape models for cardiac motion estimation

Coert Metz, Nora Baka, Hortense Kirisli, Michiel Schaap, Theo van Walsum, Stefan Klein, Lisan Neefjes, Nico Mollet, Boudewijn Lelieveldt, Marleen de Bruijne, Wiro Niessen

Department of Computer Science

10 Citations (Scopus)

Abstract

We propose a conditional statistical shape model to predict patient specific cardiac motion from the 3D end-diastolic CTA scan. The model is built from 4D CTA sequences by combining atlas based segmentation and 4D registration. Cardiac motion estimation is, for example, relevant in the dynamic alignment of pre-operative CTA data with intra-operative X-ray imaging. Due to a trend towards prospective electrocardiogram gating techniques, 4D imaging data, from which motion information could be extracted, is not commonly available. The prediction of motion from shape information is thus relevant for this purpose. Evaluation of the accuracy of the predicted motion was performed using CTA scans of 50 patients, showing an average accuracy of 1.1 mm.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention - MICCAI 2010 : 13th International Conference, Beijing, China, September 20-24, 2010, Proceedings, Part I
Editors	Tianzi Jiang, Nassir Navab, Josien P. W. Pluim, Max A. Viergever
Number of pages	8
Volume	Part I
Publisher	Springer
Publication date	2010
Pages	452-459
ISBN (Print)	978-3-642-15704-2
ISBN (Electronic)	978-3-642-15705-9
DOIs	https://doi.org/10.1007/978-3-642-15705-9_55
Publication status	Published - 2010
Event	13th International Conference on Medical Image Computing and Computer Assisted Intervention - Beijing, China Duration: 20 Sept 2010 → 24 Sept 2010 Conference number: 13

Conference

Conference	13th International Conference on Medical Image Computing and Computer Assisted Intervention
Number	13
Country/Territory	China
City	Beijing
Period	20/09/2010 → 24/09/2010

Series	Lecture notes in computer science
Number	6361
ISSN	0302-9743

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Metz, C., Baka, N., Kirisli, H., Schaap, M., van Walsum, T., Klein, S., Neefjes, L., Mollet, N., Lelieveldt, B., de Bruijne, M., & Niessen, W. (2010). Conditional shape models for cardiac motion estimation. In T. Jiang, N. Navab, J. P. W. Pluim, & M. A. Viergever (Eds.), Medical Image Computing and Computer-Assisted Intervention - MICCAI 2010: 13th International Conference, Beijing, China, September 20-24, 2010, Proceedings, Part I (Vol. Part I, pp. 452-459). Springer. Lecture notes in computer science No. 6361 https://doi.org/10.1007/978-3-642-15705-9_55

Conditional shape models for cardiac motion estimation. / Metz, Coert; Baka, Nora; Kirisli, Hortense et al.

Medical Image Computing and Computer-Assisted Intervention - MICCAI 2010: 13th International Conference, Beijing, China, September 20-24, 2010, Proceedings, Part I. ed. / Tianzi Jiang; Nassir Navab; Josien P. W. Pluim; Max A. Viergever. Vol. Part I Springer, 2010. p. 452-459 (Lecture notes in computer science; No. 6361).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Metz, C, Baka, N, Kirisli, H, Schaap, M, van Walsum, T, Klein, S, Neefjes, L, Mollet, N, Lelieveldt, B, de Bruijne, M & Niessen, W 2010, Conditional shape models for cardiac motion estimation. in T Jiang, N Navab, JPW Pluim & MA Viergever (eds), Medical Image Computing and Computer-Assisted Intervention - MICCAI 2010: 13th International Conference, Beijing, China, September 20-24, 2010, Proceedings, Part I. vol. Part I, Springer, Lecture notes in computer science, no. 6361, pp. 452-459, 13th International Conference on Medical Image Computing and Computer Assisted Intervention, Beijing, China, 20/09/2010. https://doi.org/10.1007/978-3-642-15705-9_55

Metz C, Baka N, Kirisli H, Schaap M, van Walsum T, Klein S et al. Conditional shape models for cardiac motion estimation. In Jiang T, Navab N, Pluim JPW, Viergever MA, editors, Medical Image Computing and Computer-Assisted Intervention - MICCAI 2010: 13th International Conference, Beijing, China, September 20-24, 2010, Proceedings, Part I. Vol. Part I. Springer. 2010. p. 452-459. (Lecture notes in computer science; No. 6361). doi: 10.1007/978-3-642-15705-9_55

Metz, Coert ; Baka, Nora ; Kirisli, Hortense et al. / Conditional shape models for cardiac motion estimation. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2010: 13th International Conference, Beijing, China, September 20-24, 2010, Proceedings, Part I. editor / Tianzi Jiang ; Nassir Navab ; Josien P. W. Pluim ; Max A. Viergever. Vol. Part I Springer, 2010. pp. 452-459 (Lecture notes in computer science; No. 6361).

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abstract = "We propose a conditional statistical shape model to predict patient specific cardiac motion from the 3D end-diastolic CTA scan. The model is built from 4D CTA sequences by combining atlas based segmentation and 4D registration. Cardiac motion estimation is, for example, relevant in the dynamic alignment of pre-operative CTA data with intra-operative X-ray imaging. Due to a trend towards prospective electrocardiogram gating techniques, 4D imaging data, from which motion information could be extracted, is not commonly available. The prediction of motion from shape information is thus relevant for this purpose. Evaluation of the accuracy of the predicted motion was performed using CTA scans of 50 patients, showing an average accuracy of 1.1 mm.",

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AU - Metz, Coert

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AU - Neefjes, Lisan

AU - Mollet, Nico

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AU - Niessen, Wiro

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AB - We propose a conditional statistical shape model to predict patient specific cardiac motion from the 3D end-diastolic CTA scan. The model is built from 4D CTA sequences by combining atlas based segmentation and 4D registration. Cardiac motion estimation is, for example, relevant in the dynamic alignment of pre-operative CTA data with intra-operative X-ray imaging. Due to a trend towards prospective electrocardiogram gating techniques, 4D imaging data, from which motion information could be extracted, is not commonly available. The prediction of motion from shape information is thus relevant for this purpose. Evaluation of the accuracy of the predicted motion was performed using CTA scans of 50 patients, showing an average accuracy of 1.1 mm.

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Conditional shape models for cardiac motion estimation

Abstract

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