Detection of outlier lesions based on extracted features from skin images
First Claim
Patent Images
1. A method for image analysis, comprising:
- receiving one or more images of a plurality of lesions captured from a body of a person;
extracting one or more features of the plurality of lesions from the one or more images;
analyzing the extracted one or more features;
wherein the analyzing comprises determining a distance between at least two lesions with respect to the extracted one or more features; and
determining whether any of the plurality of lesions is an outlier based on the analyzing;
wherein the extracting comprises;
converting an image of a lesion of the plurality of lesions into a matrix;
quantifying an amount of correspondence with each of a plurality of clinical features at a plurality of locations in the matrix, wherein the quantifying comprises determining a probability of having each of the plurality of clinical features at the plurality of locations in the matrix; and
digitally transforming the image of the lesion into a clinical based image representation representing one or more structural properties of the lesion, wherein the digitally transforming comprises merging the quantified amounts of correspondence with each of the plurality of clinical features;
wherein the method is performed by at least one computer system comprising at least one memory and at least one processor coupled to the memory.
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Abstract
A method for image analysis comprises receiving one or more images of a plurality of lesions captured from a body of a person, extracting one or more features of the plurality of lesions from the one or more images, analyzing the extracted one or more features, wherein the analyzing comprises determining a distance between at least two lesions with respect to the extracted one or more features, and determining whether any of the plurality of lesions is an outlier based on the analyzing.
32 Citations
19 Claims
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1. A method for image analysis, comprising:
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receiving one or more images of a plurality of lesions captured from a body of a person; extracting one or more features of the plurality of lesions from the one or more images; analyzing the extracted one or more features; wherein the analyzing comprises determining a distance between at least two lesions with respect to the extracted one or more features; and determining whether any of the plurality of lesions is an outlier based on the analyzing; wherein the extracting comprises; converting an image of a lesion of the plurality of lesions into a matrix; quantifying an amount of correspondence with each of a plurality of clinical features at a plurality of locations in the matrix, wherein the quantifying comprises determining a probability of having each of the plurality of clinical features at the plurality of locations in the matrix; and digitally transforming the image of the lesion into a clinical based image representation representing one or more structural properties of the lesion, wherein the digitally transforming comprises merging the quantified amounts of correspondence with each of the plurality of clinical features; wherein the method is performed by at least one computer system comprising at least one memory and at least one processor coupled to the memory. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A system for image analysis, comprising:
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a memory and at least one processor coupled to the memory, wherein the at least one processor is configured to; receive one or more images of a plurality of lesions captured from a body of a person; extract one or more features of the plurality of lesions from the one or more images; analyze the extracted one or more features; wherein the analyzing comprises determining a distance between at least two lesions with respect to the extracted one or more features; and determine whether any of the plurality of lesions is an outlier based on the analyzing; wherein in performing the extracting the processor is configured to; convert an image of a lesion of the plurality of lesions into a matrix; quantify an amount of correspondence with each of a plurality of clinical features at a plurality of locations in the matrix, wherein the quantifying comprises determining a probability of having each of the plurality of clinical features at the plurality of locations in the matrix; and digitally transform the image of the lesion into a clinical based image representation representing one or more structural properties of the lesion, wherein the digitally transforming comprises merging the quantified amounts of correspondence with each of the plurality of clinical features. - View Dependent Claims (13, 14, 15, 16, 17, 18)
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19. A computer program product for image analysis, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising:
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receiving one or more images of a plurality of lesions captured from a body of a person; extracting one or more features of the plurality of lesions from the one or more images; analyzing the extracted one or more features; wherein the analyzing comprises determining a distance between at least two lesions with respect to the extracted one or more features; and determining whether any of the plurality of lesions is an outlier based on the analyzing; wherein the extracting comprises; converting an image of a lesion of the plurality of lesions into a matrix; quantifying an amount of correspondence with each of a plurality of clinical features at a plurality of locations in the matrix, wherein the quantifying comprises determining a probability of having each of the plurality of clinical features at the plurality of locations in the matrix; and digitally transforming the image of the lesion into a clinical based image representation representing one or more structural properties of the lesion, wherein the digitally transforming comprises merging the quantified amounts of correspondence with each of the plurality of clinical features.
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Specification