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. 2009:779-782.
doi: 10.1109/ISBI.2009.5193165.

Mitral Annulus Segmentation from Three-Dimensional Ultrasound

Robert J Schneider  1 , Douglas P Perrin, Nikolay V Vasilyev, Gerald R Marx, Pedro J Del Nido, Robert D Howe
Affiliations

Mitral Annulus Segmentation from Three-Dimensional Ultrasound

Robert J Schneider et al. Proc IEEE Int Symp Biomed Imaging. 2009.

Abstract

An accurate and reproducible segmentation of the mitral valve annulus from 3D ultrasound is useful to clinicians and researchers in applications such as pathology diagnosis and mitral valve modeling. Current segmentation methods, however, are based on 2D information, resulting in inaccuracies and a lack of spatial coherence. We present a segmentation algorithm which, given a single user-specified point near the center of the valve, uses max-flow and active contour methods to delineate the annulus geometry in 3D. Preliminary comparisons to manual segmentations and a sensitivity study show the algorithm is both accurate and robust.

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Figures

Figure 1
Figure 1. MVA segmentation algorithm flow chart
Figure 2
Figure 2
Corresponding views of a slice through a 3DUS volume showing the original intensity (left) and the TTD (right). (LA: Left Atrium; LV: Left Ventricle; MVL: Mitral Valve Leaflets; MVA: Mitral Valve Annulus)
Figure 3
Figure 3. Example of cylindrical boundary for the graph (left) and a 2D representation of graph position and orientation along with the source and sink nodes (right)
Figure 4
Figure 4. (Left to Right) 2D view of MVsurf (black) and regions used to form PRJINT (white), PRJINT, and PRJTTD
Figure 5
Figure 5. Snake construction (left), and initialization and convergence system with multisnakes (right)
Figure 6
Figure 6. Comparison of a semi-automatically segmented MVA (solid line) to a manually segmented MVA (points)
See this image and copyright information in PMC

References

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