Abstract
We present a fully automated method to estimate the location and orientation of the left ventricle (LV) in four-dimensional (4D) cardiac magnetic resonance (CMR) images without any user input. The method is based on low-level image processing techniques incorporating anatomical knowledge and is able to provide rapid, robust feedback for automated scan planning or further processing. The method relies on a novel combination of temporal Fourier analysis of image cines with simple contour detection to achieve a fast localization of the heart. Quantitative validation was performed using 4D CMR datasets from 330 patients (54024 images) with a range of cardiac and vascular disease by comparing manual location with the automatic results. The method failed on one case, and showed average bias and precision of under 5mm in apical, mid-ventricular and basal slices in the remaining 329. The errors in automatic orientation were similar to the errors in scan planning as performed by experienced technicians.
Chapter PDF
Similar content being viewed by others
Keywords
- Cardiac Magnetic Resonance
- Orientation Error
- Cardiac Magnetic Resonance Examination
- Middle Slice
- SPAMM Image
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Santarelli, M., Positano, V., Michelassi, C., Lombardi, M., Landini, L.: Automated cardiac MR image segmentation: theory and measurement evaluation. Med. Eng. Phys. 25, 149–159 (2003)
Lorenzo-Valdés, M., Sanchez-Ortiz, G., Mohiaddin, R., Rueckert, D.: Segmentation of 4D cardiac MR images using a probabilistic atlas and the EM algorithm. In: Ellis, R.E., Peters, T.M. (eds.) MICCAI 2003. LNCS, vol. 2878, pp. 440–450. Springer, Heidelberg (2003)
Mitchell, S., Bosch, J., Lelieveldt, B., van der Geest, R., Reiber, J., Sonka, M.: 3-D active appearance models: Segmentation of cardiac MR and ultrasound images. IEEE Trans. Med. Imag. 21(9), 1167–1178 (2002)
Kaus, M.R., von Berg, J., Niessen, W., Pekar, V.: Automated Segmentation of the Left Ventricle in Cardiac MRI. In: Ellis, R.E., Peters, T.M. (eds.) MICCAI 2003. LNCS, vol. 2878, pp. 432–439. Springer, Heidelberg (2003)
Montillo, A., Metaxas, D., Axel, L.: Automated Segmentation of the Left and Right Ventricles in 4D Cardiac SPAMM Images. In: Dohi, T., Kikinis, R. (eds.) MICCAI 2002. LNCS, vol. 2488, pp. 620–633. Springer, Heidelberg (2002)
Spreeuwers, L., Breeuwer, M.: Automatic detection of the myocardial boundaries of the right and left ventricle. SPIE: Med. Imag. 4322, 1207–1217 (2001)
Danilouchkine, M., Westenberg, J., Reiber, J., Lelieveldt, B.: Accuracy of short-axis cardiac MRI automatically derived from scout acquisitions in free-breathing and breath-holding modes. MAGMA 18, 7–18 (2005)
Jackson, C., Robson, M., Francis, J., Noble, J.: Automatic Planning of the Acquisition of Cardiac MR Images. In: Ellis, R.E., Peters, T.M. (eds.) MICCAI 2003. LNCS, vol. 2878, pp. 541–548. Springer, Heidelberg (2003)
Anderson, C.: Rationale and design of the cardiac magnetic resonance imaging substudy of the ONTARGET trial programme. J. Int. Med. Res. 33(4), 50A–57A (2005)
Young, A., Cowan, B., Thrupp, S., Hedley, W., Dell’Italia, L.: Left ventricular mass and volume: fast calculation with guide-point modeling on MR images. Radiology 216, 597–602 (2000)
Sörgel, W., Vaerman, V.: Automatic heart localization from 4D MRI datasets. SPIE: Med. Imag. 3034, 333–344 (1997)
Gering, D.T.: Automatic Segmentation of Cardiac MRI. In: Ellis, R.E., Peters, T.M. (eds.) MICCAI 2003. LNCS, vol. 2878, pp. 524–532. Springer, Heidelberg (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lin, X., Cowan, B.R., Young, A.A. (2006). Automated Detection of Left Ventricle in 4D MR Images: Experience from a Large Study. In: Larsen, R., Nielsen, M., Sporring, J. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006. MICCAI 2006. Lecture Notes in Computer Science, vol 4190. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11866565_89
Download citation
DOI: https://doi.org/10.1007/11866565_89
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44707-8
Online ISBN: 978-3-540-44708-5
eBook Packages: Computer ScienceComputer Science (R0)