Order Statistic Based Cardiac Boundary Detection in 3D+t Echocardiograms
We propose a boundary detector for echocardiographic images to be used in conjunction with deformable models. It is well suited to detect endocardial and epicardial boundaries in both 2D and 3D images. We demonstrate its capabilities on an example of Active Shape Models, where it is used as a force driving the mesh towards the cardiac walls. Although the proposed approach is mostly specific to echocardiography, it does not require any training to learn the image appearance (since construction of a training set of echocardiograms is very difficult and error prone). The detector is based on computing the medians of a series of neighborhoods and analyzing the change in their values to look for the evidence of an edge. The proposed algorithm was tested on thirty 3D echocardiographic sequences (corresponding to 10 healthy and 10 dyssinchronous hearts, the latter imaged at two stages of cardiac resynchronization therapy: before and at twelve month followup).
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- 3.Frangi, A.F., et al.: A survey of three-dimensional modeling techniques for quantitative functional analysis of cardiac images. In: Advanced Image Processing in Magnetic Resonance Imaging, CRC Press, Boca Raton (2005)Google Scholar
- 6.Angelini, E.D., et al.: State-of-the-art of levelset methods in segmentation and registration of medical imaging modalities. In: Handbook of Biomedical Image Analysis, vol. 3, Kluwer Academic Publishers, Dordrecht (2005)Google Scholar
- 9.Bovik, A.C., Munson, D.C.: Edge detection using median comparisons. Comput. Vis. Image Understand. 33(3), 377–389 (1986)Google Scholar
- 11.Slabaugh, G., et al.: Information-theoretic feature detection in ultrasound images. In: Proc. EMBS, pp. 2638–2642 (2006)Google Scholar
- 12.Cootes, T., Taylor, C.: Active shape models – smart snakes. In: Proc. BMVC, pp. 266–275 (1992)Google Scholar
- 13.Ordas, S., et al.: A statistical shape model of the heart and its application to model-based segmentation. In: Proc. SPIE, vol. 6511 (2007)Google Scholar
- 14.Frigge, M., et al.: Some implementations of the boxplot. American Statistician 43(1), 50–54 (1989)Google Scholar
- 17.Yang, L., et al.: 3D ultrasound tracking of the left ventricle using one-step forward prediction and data fusion of collaborative trackers. In: Proc. CVPR, pp. 1–8 (2008)Google Scholar