Abstract
Analysis of echocardiograms is a valuable tool for assessing myocardial function and diseases. Processing of ultrasound data is challenging due to noise levels and depth-dependent quality of structure edges. We propose to adapt a method based on quadrature filters that is invariant to changes in intensity and has been successfully applied to MRI data earlier. Quadrature-filter-based registration derives the spatial deformation between two images from the local phase shift. Because the local phase is intensity-invariant and requires inhomogeneity, e.g., noise and intensity variations, to properly pick up phase shifts, it is well suited for ultrasound data. A multi-resolution and multi-scale scheme is used to cover different scales of deformations. The type and strength of regularization of the dense deformation field can be specified for each level, allowing for weighting of global and local motion. To speed up the registration, deformation fields are determined slice-wise for three orientations of the original data and subsequently combined into a true 3D deformation field. The method is evaluated with the data and ground truth provided by the Cardiac Motion Analysis Challenge at STACOM 2012.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Knutsson, H., Andersson, M.: Morphons: Segmentation using elastic canvas and paint on priors. In: Symposium on Image Analysis, SSBA 2005, pp. 73–76 (2005)
Petterson, J.: Automatic Generation of Patient Specific Models for Hip Surgery Simulation. Ph.D. thesis, Linköping University (2006)
Tautz, L., Hennemuth, A., Andersson, M., Seeger, A., Knutsson, H., Friman, O.: Phase-based non-rigid registration of myocardial perfusion MRI image sequences. In: 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp. 516–519 (April 2010)
Tautz, L., Hennemuth, A., Peitgen, H.-O.: Motion Analysis with Quadrature Filter Based Registration of Tagged MRI Sequences. In: Camara, O., Konukoglu, E., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds.) STACOM 2011. LNCS, vol. 7085, pp. 78–87. Springer, Heidelberg (2012)
Tobon-Gomez, C., De Craene, M., McLeod, K., Tautz, L., Shi, W., Hennemuth, A., Prakosa, A., Wang, H., Carr-White, G., Kapetanakis, S., Lutz, A., Rasche, V., Schaeffter, T., Butakoff, C., Friman, O., Mansi, T., Sermesant, M., Zhuang, X., Ourselin, S., Peitgen, H.O., Pennec, X., Razavi, R., Rueckert, D., Frangi, A., Rhode, K.: Evaluation of current algorithms for myocardial tracking and deformation: 1st cardiac motion analysis challenge (2012) (submittted)
Wang, Y., Georgescu, B., Houle, H., Comaniciu, D.: Volumetric Myocardial Mechanics from 3D+t Ultrasound Data with Multi-model Tracking. In: Camara, O., Pop, M., Rhode, K., Sermesant, M., Smith, N., Young, A. (eds.) STACOM-CESC 2010. LNCS, vol. 6364, pp. 184–193. Springer, Heidelberg (2010)
Zhang, Z., Song, X., Sahn, D.J.: Cardiac Motion Estimation from 3D Echocardiography with Spatiotemporal Regularization. In: Metaxas, D.N., Axel, L. (eds.) FIMH 2011. LNCS, vol. 6666, pp. 350–358. Springer, Heidelberg (2011)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tautz, L., Hennemuth, A., Peitgen, HO. (2013). Quadrature Filter Based Motion Analysis for 3D Ultrasound Sequences. In: Camara, O., Mansi, T., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds) Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. STACOM 2012. Lecture Notes in Computer Science, vol 7746. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36961-2_20
Download citation
DOI: https://doi.org/10.1007/978-3-642-36961-2_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36960-5
Online ISBN: 978-3-642-36961-2
eBook Packages: Computer ScienceComputer Science (R0)