Method of determining alignment of images in high dimensional feature space
First Claim
1. A method of determining alignment of decorelating images in high dimensional feature space, said method comprising:
- simultaneously registering a source image of a reference modality to a plurality of target images of a second modality with an algorithm based upon a measure of information affinity present in both of the source and target images to create a registered image;
extracting a plurality of feature vectors from the registered image for each of the source and target images;
plotting a distribution of the feature vectors on an entropic graph;
determining edge lengths between the feature vectors from the entropic graph; and
determining a similarity measure of one of an α
-divergence estimate or an α
-affinity estimate based upon these edge lengths to indicate whether the source and target images are sufficiently registered.
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Accused Products
Abstract
A method determines alignment of images in high dimensional feature space. The method comprises registering a source image of a reference modality to a target image of a second modality with an algorithm based upon a measure of information affinity present in both of the source and target image to create a registered image. Next, a plurality of feature vector are extracted from the registered image for each of the source and target images and attributes of the joint distribution of feature vector are captured using an entropic graph spanning the features. Edge lengths are between proximal feature vectors are extracted from the entropic graph and a similarity measure of one of an α-divergence estimate or an α-affinity estimate is constructed based upon these edge lengths to quantify whether the source and target image are sufficiently registered.
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Citations
19 Claims
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1. A method of determining alignment of decorelating images in high dimensional feature space, said method comprising:
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simultaneously registering a source image of a reference modality to a plurality of target images of a second modality with an algorithm based upon a measure of information affinity present in both of the source and target images to create a registered image; extracting a plurality of feature vectors from the registered image for each of the source and target images; plotting a distribution of the feature vectors on an entropic graph; determining edge lengths between the feature vectors from the entropic graph; and determining a similarity measure of one of an α
-divergence estimate or an α
-affinity estimate based upon these edge lengths to indicate whether the source and target images are sufficiently registered. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A method of determining alignment of decorelating images in high dimensional feature space, said method comprising:
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simultaneously registering more than two images comprising at least a source image of a reference modality to target images of a second modality with an algorithm based upon a measure of mutual information present in both of the source and target images to create a registered image; extracting a plurality of feature vectors from the registered image for each of the source and target images; determining edge lengths between proximal feature vectors from an entropic graph; and determining a similarity measure of one of an α
-divergence estimate or an α
-affinity estimate based upon these edge lengths with at least one of an α
-mutual information (α
-MI), an α
-geometric-arithmetic (α
-GA) divergence, and a Henze-Penrose (HP) divergence. - View Dependent Claims (13, 14, 15, 16)
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17. A computer readable recording medium storing an executable control program for executing a method of determining alignment of decorelating images in high dimensional feature space, said method comprising:
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simultaneously registering more than two images with an algorithm based upon a measure of information affinity present in the images to create a registered image; extracting a plurality of feature vectors from the registered image for each of the source and target images; determining edge lengths between proximal feature vectors from an entropic graph; and determining a similarity measure of one of an α
-divergence estimate or an α
-affinity estimate based upon these edge lengths to indicate whether the source and target images are sufficiently registered. - View Dependent Claims (18, 19)
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Specification