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US 12,620,106 B2Granted
MRI-based textural analysis of trabecular bone
AssigneeNew York Society for the Relief of the Ruptured and Crippled, Maintaining the Hospital for Special Surgery
InventorsEmily M. Stein, Ryan Breighner, Matthew F. Koff
Life of this patent
Estimating the term…
Abstract
In an example method, a computer system receives one or more images of one or more bones of a patient. The one or more images are generated by a magnetic resonance imaging (MRI). The computer system determines one or more metrics indicative of an image texture of the one or more images; and determines at least one of a bone risk or a bone health of the patient based on the one or more metrics.
Claims13
A method comprising:
- receiving, by a computer system, one or more images of one or more bones of a patient, wherein the one or more images are generated by a magnetic resonance imaging (MRI);
- determining, by the computer system, a plurality of first metrics indicative of an image texture of the one or more images, wherein the plurality of first metrics comprises:
- an inverse difference moment associated with the one or more images, wherein the inverse difference moment is associated with a plurality of spatial directions,
- an angular second moment of the one or more images,
- a contrast of the one or more images, and
- an entropy associated with the one or more images;
- determining, by the computer system, at least one of a bone risk or a bone health of the patient based on the plurality of first metrics, wherein determining the bone health of the patient comprises determining a second metric that indicates at least one of (i) whether the patient suffers from osteoporosis or (ii) a bone fracture risk for the patient, wherein the second metric is a weighted sum of the plurality of first metrics,
- wherein the weighted sum of the plurality of first metrics comprises:
- a first term representing a first weight multiplied by the inverse difference moment associated with the one or more images,
- a second term representing a second weight multiplied by the angular second moment of the one or more images,
- a third term representing a third weight multiplied by the contrast of the one or more images,
- a fourth term representing a fourth weight multiplied by the entropy associated with the one or more images, and
- wherein determining the second metric comprises summing at least the first term, second term, third term, and fourth term.
10 more elements
Dependencies are inferred from the claim text.