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 comprising the image;
applying each of a plurality clinical pattern classifiers to the matrix, wherein each clinical pattern classifier corresponds to a clinical feature of a plurality of clinical features;
quantifying an amount of correspondence with each clinical feature of the plurality of clinical features at one or more locations in a plurality of output matrices respectively corresponding to each clinical pattern classifier; and
converting the image of the lesion into a clinical based image representation representing one or more structural properties of the lesion, wherein the converting comprises merging the quantified amounts from each of the plurality of output matrices to digitally transform the image of the lesion into the clinical based image representation;
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.
29 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 comprising the image; applying each of a plurality clinical pattern classifiers to the matrix, wherein each clinical pattern classifier corresponds to a clinical feature of a plurality of clinical features; quantifying an amount of correspondence with each clinical feature of the plurality of clinical features at one or more locations in a plurality of output matrices respectively corresponding to each clinical pattern classifier; and converting the image of the lesion into a clinical based image representation representing one or more structural properties of the lesion, wherein the converting comprises merging the quantified amounts from each of the plurality of output matrices to digitally transform the image of the lesion into the clinical based image representation; 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 comprising the image; apply each of a plurality clinical pattern classifiers to the matrix, wherein each clinical pattern classifier corresponds to a clinical feature of a plurality of clinical features; quantify an amount of correspondence with each clinical feature of the plurality of clinical features at one or more locations in a plurality of output matrices respectively corresponding to each clinical pattern classifier; and convert the image of the lesion into a clinical based image representation representing one or more structural properties of the lesion, wherein the converting comprises merging the quantified amounts from each of the plurality of output matrices to digitally transform the image of the lesion into the clinical based image representation. - 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 non-transitory 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 comprising the image; applying each of a plurality clinical pattern classifiers to the matrix, wherein each clinical pattern classifier corresponds to a clinical feature of a plurality of clinical features; quantifying an amount of correspondence with each clinical feature of the plurality of clinical features at one or more locations in a plurality of output matrices respectively corresponding to each clinical pattern classifier; and converting the image of the lesion into a clinical based image representation representing one or more structural properties of the lesion, wherein the converting comprises merging the quantified amounts from each of the plurality of output matrices to digitally transform the image of the lesion into the clinical based image representation.
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Specification