Classification based on characterization analysis methods and systems
AssigneesNantOmics, LLC, Nanthealth, Inc.
InventorsMustafa Jaber, Liudmila A Beziaeva, Christopher W Szeto, Bing Song
Life of this patent
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Abstract
A method at a computing device for classifying elements within an input, the method including breaking the input into a plurality of patches; for each patch: creating a vector output; applying a characterization map to select a classification bin from a plurality of classification bins; and utilizing the selected classification bin to classify the vector output to create a classified output; and compiling the classified output from each patch.
Claims22
A computer-implemented method for automated mask generation in image analysis, comprising:
- receiving a digital image;
- segmenting the digital image into a plurality of patches;
- for each patch of the plurality of patches:
- generating a feature vector;
- determining a feature density;
- selecting a classifier from a stack of classifiers based on the feature density, wherein the classifiers are indexed by feature density ranges;
- applying the selected classifier to the feature vector to generate a classification;
- compiling the classifications from all patches to generate an overall classification for the digital image;
- and
- generating a mask for the digital image based on the overall classification.
A computer-based system for automated mask generation in image analysis, comprising:
- at least one computer readable memory storing software instructions;
- at least one processor coupled with the memory and, upon execution of the software instructions, performs the following operations:
- receiving a digital image;
- segmenting the digital image into a plurality of patches;
- for each patch of the plurality of patches:
- generating a feature vector;
- determining a feature density;
- selecting a classifier from a stack of classifiers based on the feature density, wherein the classifiers are indexed by feature density ranges;
- applying the selected classifier to the feature vector to generate a classification;
- compiling the classifications from all patches to generate an overall classification for the digital image;
- and
- generating a mask for the digital image based on the overall classification.
A non-transitory computer readable medium having stored thereon executable code for execution by a processor of a computing device, the executable code comprising instructions for:
- receiving a digital image;
- segmenting the digital image into a plurality of patches;
- for each patch of the plurality of patches:
- generating a feature vector;
- determining a feature density;
- selecting a classifier from a stack of classifiers based on the feature density, wherein the classifiers are indexed by feature density ranges;
- applying the selected classifier to the feature vector to generate a classification;
- compiling the classifications from all patches to generate an overall classification for the digital image;
- and
- generating a mask for the digital image based on the overall classification.
Dependencies are inferred from the claim text.