US2019340762A1PendingUtilityA1

Skin Abnormality Monitoring Systems and Methods

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Assignee: SKINIO LLCPriority: Dec 30, 2016Filed: Jul 16, 2019Published: Nov 7, 2019
Est. expiryDec 30, 2036(~10.5 yrs left)· nominal 20-yr term from priority
G06T 2207/30096G06T 11/60G06T 7/90G06T 5/20G06T 2207/30088G06T 2207/20081G06T 7/0012G06T 2207/20084G06T 2210/22G06T 7/0014G06T 7/60
46
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Claims

Abstract

A method of monitoring skin abnormalities on a skin portion of a patient includes the steps of: receiving a first image data from an image capture device, wherein the first image data includes the first skin portion; identifying a first skin mask corresponding to the first skin portion; identifying one or more first keypoints within the first skin mask, wherein each first keypoint comprises an abnormality on a first body region within the first skin portion; receiving a second image data from an image capture device, wherein the second image data includes a second body region within a second skin portion, and wherein the first and second image data are sequentially captured; and comparing the first and second body regions of the first and second image data to match the skin mask of the first and second image data.

Claims

exact text as granted — not AI-modified
We claim: 
     
         1 . A method of monitoring skin abnormalities on a skin portion of a patient, comprising the steps of:
 receiving a first image data from an image capture device, wherein the first image data includes the first skin portion;   identifying a first skin mask corresponding to the first skin portion;   identifying one or more first keypoints within the first skin mask, wherein each first keypoint comprises an abnormality on a first body region within the first skin portion;   receiving a second image data from an image capture device, wherein the second image data includes a second body region within a second skin portion, and wherein the first and second image data are sequentially captured; and   comparing the first and second body regions of the first and second image data to match the skin mask of the first and second image data.   
     
     
         2 . The method of  claim 1 , wherein an abnormality is one of a pigmented lesion. 
     
     
         3 . The method of  claim 1 , further comprising the step of determining one or more second keypoints within the second skin mask, wherein each second keypoint comprises an abnormality on the skin portion. 
     
     
         4 . The method of  claim 1 , wherein the first keypoint is determined using a blob detection method. 
     
     
         5 . The method of  claim 1 , wherein the first keypoint is determined using the Laplacian-of-Gaussian filters. 
     
     
         6 . The method of  claim 5 , wherein two or more of the first keypoints are duplicates, and duplicate keypoints are removed. 
     
     
         7 . The method of  claim 6 , further comprising the step of merging at least two keypoints. 
     
     
         8 . The method of  claim 7 , wherein the at least two keypoints includes a first detection data and a second detection data, and
 wherein the step of merging includes obtaining a first cropped image of the first detection data, a second cropped image of the second detection data, and a third cropped image of the first and second detection data,   wherein the merging step comprises the step of performing a contour analysis of on each of the first, second, and third cropped images, and wherein if the third cropped image contains a single contour, the first and second detection data is merged.   
     
     
         9 . The method of  claim 1 , further comprising the step of computing a geometrical property for each first and second keypoints. 
     
     
         10 . The method of  claim 9 , wherein the geometrical property includes one or more of the following properties: height, width, perimeter, area, color distribution, and a dominant color. 
     
     
         11 . The method of  claim 1 , wherein at least one of the steps of determining body landmarks, merging keypoint data, and matching keypoints is repeated.

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