Image analysis method and system
AssigneeStraxcorp Pty Ltd
InventorYu PENG
Life of this patent
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Abstract
A computer-implemented image analysis method and system. The method comprises: quantifying one or more features segmented and identified from a medical image of a subject; extracting clinically relevant features from non-image data pertaining to the subject; assessing the features segmented from the medical image and the features extracted from the non-image data with a trained machine learning model; and outputting one or more results of the assessing of the features.
Claims29
A computer-implemented image analysis method, comprising:
- quantifying one or more features segmented and identified from a medical image of or including bone of a subject;
- extracting non-image data pertaining to the subject and pertinent to bone deterioration from one or more non-image data sources;
- extracting clinically relevant features from the non-image data pertaining to the subject;
- assessing bone fragility, comprising assessing the quantified features segmented from the medical image and the features extracted from the non-image data with a trained machine learning model;
- and
- outputting one or more results of the assessing of the features bone fragility;
- wherein quantifying the features comprises determining any one or more of:
- vBMD (volumetric bone mineral density) of the bone, cortical porosity, transitional region vBMD, trabecular region vBMD, matrix mineralization level, marrow adiposity, average thickness of the compact cortex, trabecular tissue separation, trabecular density, and bone volume fraction.
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An image analysis system, comprising:
- a feature quantifier configured to quantify one or more features segmented and identified from a medical image of or including bone of a subject;
- a non-image data processor configured to extract non-image data pertaining to the subject and pertinent to bone deterioration from one or more non-image data sources and to extract clinically relevant features from non-image data pertaining to the subject;
- a feature assessor configured to assess bone fragility, comprising assessing the quantified features segmented from the medical image and the features extracted from the non-image data with a trained machine learning model;
- and
- an output configured to output one or more results of the assessing of the bone fragility;
- wherein quantifying the features comprises determining any one or more of:
- vBMD (volumetric bone mineral density) of the bone, cortical porosity, transitional region vBMD, trabecular region vBMD, matrix mineralization level, marrow adiposity, average thickness of the compact cortex, trabecular tissue separation, trabecular density, and bone volume fraction.
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Dependencies are inferred from the claim text.