Skeletonization of medical images from incomplete and noisy voxel data
AssigneeBiosense Webster (Israel) Ltd.
InventorsLeonid Zaides, Fady Massarwa, Lior Zar
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Abstract
A method for generating a skeleton in an image of a cavity of an organ of a body includes receiving a map of the cavity, the map including surface voxels and interior voxels. A subset of the interior voxels is generated, of candidate locations to be on the skeleton. The subset is pruned by removing outlier candidate locations. Using a geometrical model including a statistical model, the candidate locations remaining in the pruned subset are spatially compressed. The compressed candidate locations are connected to produce one or more centerlines of the skeleton. At least the skeleton is displayed to user.
Claims22
A method for generating a skeleton in an image of a cavity of an organ of a body, the method comprising:
- receiving a map of the cavity, the map comprising surface voxels and interior voxels;
- generating a subset of the interior voxels that are candidate locations to be on the skeleton;
- pruning the subset by removing outlier candidate locations based on at least one of an angular dispersion of generative surface voxels or a variance in location of the candidate locations;
- using a geometrical model comprising a statistical model, spatially compressing the candidate locations remaining in the pruned subset;
- connecting the compressed candidate locations to produce one or more centerlines of the skeleton;
- and
- displaying at least the skeleton to user.
A system for generating a skeleton in an image of a cavity of an organ of a body, the system comprising:
- a memory configured to store a map of the cavity, the map comprising surface voxels and cavity voxels;
- and
- a processor, which is configured to:
- generate a subset of the interior voxels that are candidate locations to be on the skeleton;
- prune the subset by removing outlier candidate locations based on at least one of an angular dispersion of generative surface voxels or a variance in location of the candidate locations;
- using a geometrical model comprising a statistical model, spatially compress the candidate locations remaining in the pruned subset;
- connect the compressed candidate locations to produce one or more centerlines of the skeleton;
- and
- display at least the skeleton to user.
Dependencies are inferred from the claim text.