Fully automatic image segmentation of heart valves using multi-atlas label fusion and deformable medial modeling
US9406142B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 8, 2014 |
| Grant date | Aug 2, 2016 |
| Priority date | — |
| Expiry date | Oct 8, 2034 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2210/41
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A fully automatic method for segmentation of the mitral leaflets in 3D transesophageal echocardiographic (3D TEE) images is provided. The method combines complementary probabilistic segmentation and geometric modeling techniques to generate 3D patient-specific reconstructions of the mitral leaflets and annulus from 3D TEE image data with no user interaction. In the model-based segmentation framework, mitral leaflet geometry is described with 3D continuous medial representation (cm-rep). To capture leaflet geometry in a target 3D TEE image, a pre-defined cm-rep template of the mitral leaflets is deformed such that the negative log of a Bayesian posterior probability is minimized. The likelihood of the objective function is given by a probabilistic segmentation of the mitral leaflets generated by multi-atlas joint label fusion, while the validity constraints and regularization terms imposed by cm-rep act as shape priors that preserve leaflet topology and constrain model fitting.
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