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US 12,178,549 B2Granted
Optoacoustic image analysis method and system for automatically estimating lesion traits
AssigneeSeno Medical Instruments, Inc.
InventorsBryan Clingman, Sandra G. Dykes
Life of this patent
Estimating the term…
Abstract
A system and method for performing optoacoustic classification prediction is provided. The method utilizes one or more processors in connection with receiving OA feature scores in connection with OA images collected from a patient examination for a volume of interest. The volume of interest includes a lesion. The method applies the OA feature scores to a classification model to obtain a predictive result indicative of a trait of the lesion.
Claims13
A method for performing optoacoustic (OA) classification prediction, comprising:
- utilizing one or more processors for, receiving OA feature scores associated with OA images collected from a patient examination for a volume of interest, the volume of interest including a lesion;
- applying the OA feature scores to a classification model to obtain a predictive result indicative of a trait of the lesion, wherein the classification model was built utilizing a predictive machine learning classifier and a data set that includes OA feature scores, malignant labels and benign labels for corresponding lesions in the data set;
- and
- outputting the predictive result.
1 more element
A system for performing optoacoustic (OA) classification prediction, comprising:
- memory configured to store program instructions;
- one or more processors that, when executing the program instructions, are configured to:
- receive OA feature scores associated with OA images collected from a patient examination for a volume of interest, the volume of interest including a lesion;
- apply the OA feature scores to a classification model to obtain a predictive result indicative of a likelihood that the lesion is in a malignant class or benign class, wherein the classification model was built utilizing a predictive machine learning classifier and a data set that includes OA feature scores, malignant labels and benign labels for corresponding lesions in the data set;
- and
- output the predictive result.
3 more elements
Dependencies are inferred from the claim text.