Image registration using locally-weighted fitting
First Claim
1. A computer-implemented method for image registration, comprising:
- accepting a three-dimensional (3-D) image of an organ, the image comprising a first plurality of image points with respective image coordinates;
accepting a map defining a distribution of values of a physiological parameter over the organ, the map comprising a second plurality of map points with respective map coordinates;
associating respective confidence levels with one or more of the map coordinates and image coordinates;
assigning weights to at least some of the map points and image points responsively to the confidence levels of the respective map coordinates and image coordinates; and
fitting the 3-D image with the map by calculating a geometrical transformation between the map coordinates and the image coordinates based on the weights.
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Abstract
A computer-implemented method for image registration includes accepting a three-dimensional (3-D) image of an organ. The image includes a first plurality of image points with respective image coordinates. A map defining a distribution of values of a physiological parameter over the organ is accepted. The map includes a second plurality of map points with respective map coordinates. Confidence levels are associated with one or more of the map coordinates and image coordinates. Weights are assigned to at least some of the map points and image points responsively to the confidence levels of the respective map coordinates and image coordinates. The 3-D image is fitted with the map by calculating a geometrical transformation between the map coordinates and the image coordinates based on the weights.
60 Citations
27 Claims
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1. A computer-implemented method for image registration, comprising:
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accepting a three-dimensional (3-D) image of an organ, the image comprising a first plurality of image points with respective image coordinates;
accepting a map defining a distribution of values of a physiological parameter over the organ, the map comprising a second plurality of map points with respective map coordinates;
associating respective confidence levels with one or more of the map coordinates and image coordinates;
assigning weights to at least some of the map points and image points responsively to the confidence levels of the respective map coordinates and image coordinates; and
fitting the 3-D image with the map by calculating a geometrical transformation between the map coordinates and the image coordinates based on the weights. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. Apparatus for image registration, comprising:
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an interface, which is arranged to accept a three-dimensional (3-D) image of an organ, the image comprising a first plurality of image points with respective image coordinates, and to further accept a map defining a distribution of values of a physiological parameter over the organ, the map comprising a second plurality of map points with respective map coordinates; and
a processor, which is arranged to associate respective confidence levels with one or more of the map coordinates and image coordinates, to assign weights to at least some of the map points and image points responsively to the confidence levels of the respective map coordinates and image coordinates, and to fit the 3-D image with the map by calculating a geometrical transformation between the map coordinates and the image coordinates based on the weights. - View Dependent Claims (15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26)
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27. A computer software product for image registration, the product comprising a computer-readable medium in which instructions are stored, which instructions, when read by a computer, cause the computer to accept a pre-acquired three-dimensional (3-D) image of an organ, the image comprising a first plurality of image points with respective image coordinates, to accept a map defining a distribution of values of a physiological parameter over the organ, the map comprising a second plurality of map points with respective map coordinates, to associate respective confidence levels with one or more of the map coordinates and image coordinates, to assign weights to the map points and image points responsively to the confidence levels of the respective map coordinates and image coordinates, and to fit the 3-D image with the map by calculating a geometrical transformation between the map coordinates and the image coordinates based on the weights.
Specification