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US 10,706,548 B2Granted
Automated segmentation of organs, such as kidneys, from magnetic resonance images
AssigneeUniversity of Pittsburgh—Of the Commonwealth System of Higher Education
InventorsKyong Tae Bae, Youngwoo Kim
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Abstract
A method of segmenting an MR organ volume includes performing regional mapping on the MR organ volume using a spatial prior probability map of a location of the organ to create a regionally mapped MR organ volume, and performing boundary refinement on the regionally mapped MR organ volume using a level set framework that employs the spatial prior probability map and a propagated shape constraint to generate a segmented MR organ volume.
Claims15
A method of segmenting an MR organ volume, comprising:
- performing regional mapping on the MR organ volume using a spatial prior probability map of a location of the organ to create a regionally mapped MR organ volume, wherein the regional mapping comprises:
- preprocessing the MR organ volume by application of total variation regularization to the MR organ volume to create a TV regularized MR organ volume;
- computing magnitudes of image gradients for the TV regularized MR organ volume;
- and
- generating a map of candidate organ regions for the MR organ volume by multiplying the magnitudes of image gradients by the spatial prior probability map;
- and
- performing boundary refinement on the regionally mapped MR organ volume using a level set framework that employs the spatial prior probability map and a propagated shape constraint to generate a segmented MR organ volume.
4 more elements
A computerized system for segmenting an MR organ volume, comprising:
- a processing apparatus, wherein the processing apparatus includes:
- a spatial prior probability map component that includes a spatial prior probability map of a location of the organ;
- a regional mapping component configured for creating a regionally mapped MR organ volume by performing regional mapping on the MR organ volume using the spatial prior probability map, wherein the regional mapping component is structured and configured to, preprocess the MR organ volume by application of total variation regularization to the MR organ volume to create a TV regularized MR organ volume;
- compute magnitudes of image gradients for the TV regularized MR organ volume;
- and generate a map of candidate organ regions for the MR organ volume by multiplying the magnitudes of image gradients by the spatial prior probability map;
- and
- a boundary refinement component configured for generating a segmented MR organ volume by performing boundary refinement on the regionally mapped MR organ volume using a level set framework that employs the spatial prior probability map and a propagated shape constraint, wherein the map of candidate organ regions is used by the boundary refinement component.
4 more elements
Dependencies are inferred from the claim text.