Method for the detection and staging of liver fibrosis from image acquired data
AssigneeUniversity of Mississippi Medical Center
InventorAndrew Smith
Life of this patent
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Abstract
This invention relates to methods for ascertaining at least one of liver fibrosis or cirrhosis in a subject, by processing of one or more medical images of the liver, using a computing machine, to quantify nodularity of the surface of the liver and calculate a liver surface nodularity score.
Claims25
A method for ascertaining at least one of liver fibrosis or cirrhosis in a subject, said method comprising:
- processing of one or more medical images of the liver, using a computing machine, to quantify nodularity of the surface of the liver and calculate a liver surface nodularity score;
- and
- processing the liver surface nodularity score as a metric, wherein the process step considers at least one of an individual's computed tomography (CT), magnetic resonance (MR), or ultrasound grayscale medical images.
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A method for ascertaining at least one of liver fibrosis or cirrhosis in a subject, said method comprising:
- processing of one or more medical images of the liver, using a computing machine, to quantify nodularity of the surface of the liver and calculate a liver surface nodularity score;
- processing the liver surface nodularity score as a metric, wherein the process step considers at least one of an individual's computed tomography (CT), magnetic resonance (MR), or ultrasound grayscale medical images;
- and
- processing at least one of said medical images to acquire at least one measurement of liver volume and mathematically combining said measurement with said liver surface nodularity score to arrive at a clinically-predictive algorithm to stage liver fibrosis and/or cirrhosis.
15-28. (canceled)
A method for ascertaining at least one of liver fibrosis or cirrhosis in a subject, said method comprising:
- processing of one or more medical images of the liver, using a computing machine, to quantify nodularity of the surface of the liver and calculate a liver surface nodularity score;
- processing the liver surface nodularity score as a metric, wherein the process step considers at least one of an individual's computed tomography (CT), magnetic resonance (MR), or ultrasound grayscale medical images;
- and
- processing at least one of said medical images to acquire at least one measurement of liver morphology and mathematically combining said measurement with said liver surface nodularity score to arrive at a component clinically-predictive algorithm to stage liver fibrosis and/or cirrhosis.
Dependencies are inferred from the claim text.