COMPUTER AIDED DIAGNOSTIC SYSTEM INCORPORATING APPEARANCE ANALYSIS FOR DIAGNOSING MALIGNANT LUNG NODULES
First Claim
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1. A method of classifying a pulmonary nodule, the method comprising:
- receiving image data associated with a chest scan;
segmenting image data associated with lung tissue from the image data associated with the chest scan;
equalizing the segmented image data;
segmenting image data associated with a pulmonary nodule from the equalized and segmented image data; and
classifying the pulmonary nodule as benign or malignant by applying a learned appearance model to the segmented image data associated with the pulmonary nodule, wherein the learned appearance model is based upon visual appearances of a plurality of known pulmonary nodules.
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Abstract
A computer aided diagnostic system and automated method diagnose lung cancer through modeling and analyzing the visual appearance of pulmonary nodules. A learned appearance model used in such analysis describes the appearance of pulmonary nodules in terms of voxel-wise conditional Gibbs energies for a generic rotation and translation invariant second-order Markov-Gibbs random field (MGRF) model of malignant nodules with analytically estimated characteristic voxel neighborhoods and potentials.
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Citations
16 Claims
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1. A method of classifying a pulmonary nodule, the method comprising:
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receiving image data associated with a chest scan; segmenting image data associated with lung tissue from the image data associated with the chest scan; equalizing the segmented image data; segmenting image data associated with a pulmonary nodule from the equalized and segmented image data; and classifying the pulmonary nodule as benign or malignant by applying a learned appearance model to the segmented image data associated with the pulmonary nodule, wherein the learned appearance model is based upon visual appearances of a plurality of known pulmonary nodules. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. An apparatus, comprising:
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at least one processor; and program code configured to be executed by the at least one processor to classify a pulmonary nodule as benign or malignant by applying a learned appearance model to the segmented image data associated with the pulmonary nodule, wherein the learned appearance model is based upon visual appearances of a plurality of known pulmonary nodules.
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9. A program product, comprising:
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a computer readable storage medium; and program code stored on the computer readable storage medium and configured upon execution to classify a pulmonary nodule as benign or malignant by applying a learned appearance model to the segmented image data associated with the pulmonary nodule, wherein the learned appearance model is based upon visual appearances of a plurality of known pulmonary nodules.
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10. A method of generating a learned appearance model for classifying pulmonary nodules as benign or malignant, comprising:
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normalizing image data associated with a plurality of known pulmonary nodules; and processing the normalized image data to learn a 3D appearance of the plurality of known pulmonary nodules to generate the learned appearance model. - View Dependent Claims (11, 12, 13, 14, 15, 16)
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Specification