Database organization and searching
First Claim
1. A method comprising:
- receiving a plurality of images, each one of the plurality of images including an instance of a human body part obtained through a medical imaging technique;
registering each one of the plurality of images in a non-rigid manner to a coordinate system to superimpose one or more like features within each one of the plurality of images within the coordinate system, thereby obtaining a plurality of registered images;
labeling each one of the plurality of registered images with a label according to an observed characteristic;
obtaining one or more feature vectors from each one of the plurality of registered images; and
training a model to associate the one or more feature vectors with the label.
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Accused Products
Abstract
The database organization and searching systems disclosed herein provide techniques for organizing large-scale image data sources such as medical image databases. Database records such as medical images may be pre-processed, such as through registration, segmentation, and extraction of feature vectors, to effectively normalize data among different images. Each image, or a portion thereof, is then labeled according to some observed characteristic or other attribute. A model, such as a linear regression model, may then be trained to associate the feature vectors with the labels. The model is then available for labeling other images. In this manner, search techniques for well-organized or indexed databases may be applied automatically to databases that are not well-organized, but that have the same underlying data type. Data that is organized in this way may also be used to construct diagnostic aids or other tools.
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Citations
24 Claims
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1. A method comprising:
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receiving a plurality of images, each one of the plurality of images including an instance of a human body part obtained through a medical imaging technique;
registering each one of the plurality of images in a non-rigid manner to a coordinate system to superimpose one or more like features within each one of the plurality of images within the coordinate system, thereby obtaining a plurality of registered images;
labeling each one of the plurality of registered images with a label according to an observed characteristic;
obtaining one or more feature vectors from each one of the plurality of registered images; and
training a model to associate the one or more feature vectors with the label. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 17, 19, 20, 24)
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15. A system comprising:
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receiving means for receiving a plurality of images, each one of the plurality of images including an instance of a human body part obtained through a medical imaging technique;
registering means for registering each one of the plurality of images in a non-rigid manner to a coordinate system to superimpose one or more like features within each one of the plurality of images within the coordinate system, thereby obtaining a plurality of registered images;
labeling means for labeling each one of the plurality of registered images with a label according to an observed characteristic;
obtaining means for obtaining one or more feature vectors from each one of the plurality of registered images; and
training means for training a model to associate the one or more feature vectors with the label.
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16. A computer program product comprising:
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computer executable code for receiving a plurality of images, each one of the plurality of images including an instance of a human body part obtained through a medical imaging technique;
computer executable code for registering each one of the plurality of images in a non-rigid manner to a coordinate system to superimpose one or more like features within each one of the plurality of images within the coordinate system, thereby obtaining a plurality of registered images;
computer executable code for labeling each one of the plurality of registered images with a label according to an observed characteristic;
computer executable code for obtaining one or more feature vectors from each one of the plurality of registered images; and
computer executable code for training a model to associate the one or more feature vectors with the label.
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18. A method comprising:
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receiving a plurality of images, each one of the plurality of images including an instance of a human body part obtained through a medical imaging technique;
registering each one of the plurality of images in a non-rigid manner to a coordinate system to superimpose one or more like features within each one of the plurality of images within the coordinate system, thereby obtaining a plurality of registered images;
receiving a header for each one of the plurality of images that includes data associated with the one of the plurality of images;
obtaining one or more feature vectors from each one of the plurality of registered images;
training a model to associate the one or more feature vectors with the header; and
applying the model to identify the presence of any errors in a new header for a new image.
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21. A method comprising:
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receiving a plurality of images, each one of the plurality of images including an instance of a human body part obtained through a medical imaging technique;
registering each one of the plurality of images in a non-rigid manner to a coordinate system to superimpose one or more like features within each one of the plurality of images within the coordinate system, thereby obtaining a plurality of registered images;
obtaining one or more feature vectors from each one of the plurality of registered images;
associating a pathology with each one of the plurality of images;
training a model to associate the pathology associated with each image with the one or more feature vectors for that image; and
applying the model to identify the presence of the pathology in a new image. - View Dependent Claims (22)
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23. A method comprising:
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receiving a plurality of images, each one of the plurality of images including an instance of a human body part obtained through a medical imaging technique;
registering each one of the plurality of images in a non-rigid manner to a coordinate system to superimpose one or more like features within each one of the plurality of images within the coordinate system, thereby obtaining a plurality of registered images;
identifying one or more regions of interest in each of the plurality of registered images, the regions of interest including a pathology; and
generating a spatial probability map of locations of the pathology from the plurality of registered images and the regions of interest.
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Specification