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Proceedings Paper

Three-dimensional active shape model matching for left ventricle segmentation in cardiac CT
Author(s): Hans C. van Assen; Rob J. van der Geest; Mikhail G. Danilouchkine; Hildo J. Lamb; Johan H. C. Reiber; Boudewijn P. F. Lelieveldt
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Paper Abstract

Manual quantitative analysis of cardiac left ventricular function using multi-slice CT is labor intensive because of the large datasets. We present an automatic, robust and intrinsically three-dimensional segmentation method for cardiac CT images, based on 3D Active Shape Models (ASMs). ASMs describe shape and shape variations over a population as a mean shape and a number of eigenvariations, which can be extracted by e.g. Principal Component Analysis (PCA). During the iterative ASM matching process, the shape deformation is restricted within statistically plausible constraints (±3σ). Our approach has two novel aspects: the 3D-ASM application to volume data of arbitrary planar orientation, and the application to image data from another modality than which was used to train the model, without the necessity of retraining it. The 3D-ASM was trained on MR data and quantitatively evaluated on 17 multi-slice cardiac CT data sets, with respect to calculated LV volume (blood pool plus myocardium) and endocardial volume. In all cases, model matching was convergent and final results showed a good model performance. Bland-Altman analysis however, showed that bloodpool volume was slightly underestimated and LV volume was slightly overestimated by the model. Nevertheless, these errors remain within clinically acceptable margins. Based on this evaluation, we conclude that our 3D-ASM combines robustness with clinically acceptable accuracy. Without retraining for cardiac CT, we could adapt a model trained on cardiac MR data sets for application in cardiac CT volumes, demonstrating the flexibility and feasibility of our matching approach. Causes for the systematic errors are edge detection, model constraints, or image data reconstruction. For all these categories, solutions are discussed.

Paper Details

Date Published: 15 May 2003
PDF: 10 pages
Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); doi: 10.1117/12.481314
Show Author Affiliations
Hans C. van Assen, Leiden Univ. Medical Ctr. (Netherlands)
Rob J. van der Geest, Leiden Univ. Medical Ctr. (Netherlands)
Mikhail G. Danilouchkine, Leiden Univ. Medical Ctr. (Netherlands)
Hildo J. Lamb, Leiden Univ. Medical Ctr. (Netherlands)
Johan H. C. Reiber, Leiden Univ. Medical Ctr. (Netherlands)
Boudewijn P. F. Lelieveldt, Leiden Univ. Medical Ctr. (Netherlands)

Published in SPIE Proceedings Vol. 5032:
Medical Imaging 2003: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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