Abstract
Heart failures (cardiac infarction) are of increasing importance due to increasing life expectation. For clinical diagnosis parameters for the condition of hearts are needed and can be derived automatically by imaging processing. In this work we present an efficient method to segment the left ventricle (LV) in heart MR data from rats using two linked active contour models working in a spherical coordinate system. The initial model used for the active contour scheme is generated from user given points by a radial interpolation algorithm. The model was developed on healthy heart data and was tested on 15 different data sets and the results are presented.
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References
Chen CW, Huang TS, Arrott M. Modeling, Analysis, and Visualization of Left Ventricle Shape and Motion by Hierarchical Decomposition. IEEE Transactions on Pattern Analysis and Machine Intelligence 1994;16(4):342–356.
Rueckert D, Burger P. Shape-based Segmentation and Tracking in 4D Cardiac MR Images. In: Lecture Notes in Computer Science. vol. 1205. Springer-Verlag; 1997.
Pluempitiwiriyawej C. Cardiac MR Image Segmentation: STACS, A New Active Contour Scheme. Ph.D. thesis. Carnegie Mellon University, Pittsburgh, PA 15213; 2003.
Bardinet E, Cohen LD, Ayache N. A parametric deformable model to fit unstructured 3d data. Computer Vision and Image Understanding 1998;71(1):39–54.
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© 2005 Springer-Verlag Berlin Heidelberg
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Schildt, M., Pohle, R., Brune, K., Hess, A. (2005). Semi-automatic Segmentation of the Left Ventricle in CINE MR Datasets by Linked Radial Active Model (LRAM). In: Meinzer, HP., Handels, H., Horsch, A., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2005. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-26431-0_26
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DOI: https://doi.org/10.1007/3-540-26431-0_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25052-4
Online ISBN: 978-3-540-26431-6
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