Methods and systems for performing model-based image processing
AssigneeGeneral Electric Company
InventorsJean-Baptiste Thibault, Ruoqiao Zhang, Charles Bouman, Ken Sauer
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Abstract
Methods and systems for model-based image processing are provided. One method includes selecting at least one reference image from a plurality of reference images, partitioning the at least one reference image into a plurality of patches, generating a probability distribution for each of the patches, and generating a model of a probability distribution for the at least one reference image using the probability distributions for each of the patches.
Claims27
A method of generating a model for image processing, said method comprising:
- selecting at least one reference image from a plurality of reference images;
- partitioning the at least one reference image into a plurality of patches;
- generating a probability distribution for each of the patches;
- and
- generating a model of a probability distribution for the at least one reference image using the probability distributions for each of the patches.
A non-transitory computer readable medium programmed to instruct a computer of a Computed Tomography (CT) system to:
- receive a user input selecting at least one reference image from a plurality of reference images;
- automatically partition the at least one reference image into a plurality of patches;
- generate a probability distribution for each of the patches;
- and
- generate a model of a probability distribution for the at least one reference image using the probability distributions for each of the patches.
A computed tomography (CT) imaging system comprising:
- a detector configured to output x-ray attenuation information;
- and
- a processor coupled to the detector, the processor being configured to:
- receive a user input selecting at least one reference image from a plurality of reference images;
- automatically partition the at least one reference image into a plurality of patches;
- generate a probability distribution for each of the patches;
- and
- generate a model of a probability distribution for the at least one reference image using the probability distributions for each of the patches.
Dependencies are inferred from the claim text.