Automatic ground truth generation for medical image collections
First Claim
1. A method for automatic ground truth generation of medical image collections, the method comprising:
- receiving a plurality of imaging studies, wherein each imaging study comprises one or more images and a textual report associated with the one or more images;
selecting a key image from each of the plurality of imaging studies;
extracting one or more discriminating image features from a region of interest within the key image;
processing the textual report associated with the one or more images to detect one or more concept labels;
assigning an initial label from the one or more concept labels to the one or more discriminating image features; and
learning an association between each of the one or more discriminating image features and the one or more concept labels;
wherein learning the association between each of the one or more discriminating image features and the one or more concept labels comprises executing a convex optimization learning algorithm.
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Abstract
Methods and arrangements for automatic ground truth generation of medical image collections. Aspects include receiving a plurality of imaging studies, wherein each imaging study includes one or more images and a textual report associated with the one or more images. Aspects also include selecting a key image from each of the one or more images from each of the plurality of imaging studies and extracting one or more discriminating image features from a region of interest within the key image. Aspects further include processing the textual report associated with the one or more images to detect one or more concept labels, assigning an initial label from the one or more concept labels to the one or more discriminating image features, and learning an association between each of the one or more discriminating image features and the one or more concept labels.
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Citations
18 Claims
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1. A method for automatic ground truth generation of medical image collections, the method comprising:
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receiving a plurality of imaging studies, wherein each imaging study comprises one or more images and a textual report associated with the one or more images; selecting a key image from each of the plurality of imaging studies; extracting one or more discriminating image features from a region of interest within the key image; processing the textual report associated with the one or more images to detect one or more concept labels; assigning an initial label from the one or more concept labels to the one or more discriminating image features; and learning an association between each of the one or more discriminating image features and the one or more concept labels; wherein learning the association between each of the one or more discriminating image features and the one or more concept labels comprises executing a convex optimization learning algorithm. - View Dependent Claims (2, 3, 4, 5, 6)
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7. A computer program product for automatic ground truth generation of medical image collections, the computer program product comprising:
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a computer readable storage medium having program code embodied therewith, the program code executable by a computer to; receive a plurality of imaging studies, wherein each imaging study comprises one or more images and a textual report associated with the one or more images; select a key image from each of the one or more images from each of the plurality of imaging studies; extract one or more discriminating image features from a region of interest within the key image; process the textual report associated with the one or more images to detect one or more concept labels; assign an initial label from the one or more concept labels to the one or more discriminating image features; and learn an association between each of the one or more discriminating image features and the one or more concept labels; wherein learning the association between each of the one or more discriminating image features and the one or more concept labels comprises executing a convex optimization learning algorithm. - View Dependent Claims (8, 9, 10, 11, 12)
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13. A computer system for automatic ground truth generation of medical image collections, the computer system comprising:
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a processor configured to execute a program code causing the computer system to; receive a plurality of imaging studies, wherein each imaging study comprises one or more images and a textual report associated with the one or more images; select a key image from each of the plurality of imaging studies; extract one or more discriminating image features from a region of interest within the key image; process the textual report associated with the one or more images to detect one or more concept labels; assign an initial label from the one or more concept labels to the one or more discriminating image features; and learn an association between each of the one or more discriminating image features and the one or more concept labels; wherein learning the association between each of the one or more discriminating image features and the one or more concept labels comprises executing a convex optimization learning algorithm. - View Dependent Claims (14, 15, 16, 17, 18)
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Specification