Device and method for classifying a condition based on image analysis
First Claim
Patent Images
1. A device comprising:
- circuitry configured to;
receive one or more input images;
detect a plurality of anatomical landmarks on the one or more input images using a pre-determined face model, by generating a statistical shape with non-Gaussian shape prior estimation using kernel density estimation (KDE) and/or Gaussian mixture model (GMM);
extract a plurality of geometric and local texture features based on the plurality of anatomical landmarks;
select one or more features from the plurality of geometric and local texture features; and
determine a likelihood that a patient in the one or more input images has a genetic disorder based on the selected one or more features.
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Abstract
An image analysis device includes circuitry that receives one or more input images and detects a plurality of anatomical landmarks on the one or more input images using a pre-determined face model. The circuitry extracts a plurality of geometric and local texture features based on the plurality of anatomical landmarks. The circuitry selects one or more condition-specific features from the plurality of geometric and local texture features. The circuitry classifies the one or more input images into one or more conditions based on the one or more condition-specific features.
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Citations
27 Claims
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1. A device comprising:
circuitry configured to; receive one or more input images; detect a plurality of anatomical landmarks on the one or more input images using a pre-determined face model, by generating a statistical shape with non-Gaussian shape prior estimation using kernel density estimation (KDE) and/or Gaussian mixture model (GMM); extract a plurality of geometric and local texture features based on the plurality of anatomical landmarks; select one or more features from the plurality of geometric and local texture features; and determine a likelihood that a patient in the one or more input images has a genetic disorder based on the selected one or more features. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24)
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25. A method comprising:
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receiving one or more input images; detecting, by circuitry, a plurality of anatomical landmarks on the one or more input images using a pre-determined face model, the detecting including generating a statistical shape with non-Gaussian shape prior estimation using kernel density estimation (KDE) and/or Gaussian mixture model (GMM); extracting, by the circuitry, a plurality of geometric and local texture features based on the plurality of anatomical landmarks; selecting, by the circuitry, one or more features from the plurality of geometric and local texture features; and determining, by the circuitry, a likelihood that a patient in the one or more input images has a genetic disorder based on the selected one or more features.
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26. A non-transitory computer readable medium having instructions stored therein that when executed by one or more processors cause a computer to perform a method comprising:
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receiving one or more input images; detecting a plurality of anatomical landmarks on the one or more input images using a pre-determined face model, the detecting including generating a statistical shape with non-Gaussian shape prior estimation using kernel density estimation (KDE) and/or Gaussian mixture model (GMM); extracting a plurality of geometric and local texture features based on the plurality of anatomical landmarks; selecting one or more features from the plurality of geometric and local texture features; and determining a likelihood that a patient in the one or more input images has a genetic disorder based on the selected one or more features.
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27. A system comprising:
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circuitry configured to; receive one or more input images; detect a plurality of anatomical landmarks on the one or more input images using a pre-determined face model, by generating a statistical shape with non-Gaussian shape prior estimation using kernel density estimation (KDE) and/or Gaussian mixture model (GMM); extract a plurality of geometric and local texture features based on the plurality of anatomical landmarks; select one or more features from the plurality of geometric and local texture features; and determine a likelihood that a patient in the one or more input images has a genetic disorder based on the selected one or more features; and a device that captures the one or more input images and transmits the one or more input images to the circuitry.
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Specification