Abstract: A process for assessing image quality metrics includes the steps of receiving image data from an image capture device, wherein the image data includes a skin portion; extracting, via a machine learning system, a first set of information from the image data; extracting, via the machine learning system, a second set of information from the image data; scoring the first and second sets of information of the image data to reflect image quality metrics; identifying a threshold score reflecting acceptable image quality metrics; when the score is greater than the threshold score, submit the image data; and when the score is less than the threshold score, prompt the user to retake the image data.

Abstract: A process for assessing image quality metrics includes the steps of receiving image data from an image capture device, wherein the image data includes a skin portion; extracting, via a machine learning system, a first set of information from the image data; extracting, via the machine learning system, a second set of information from the image data; scoring the first and second sets of information of the image data to reflect image quality metrics; identifying a threshold score reflecting acceptable image quality metrics; when the score is greater than the threshold score, submit the image data; and when the score is less than the threshold score, prompt the user to retake the image data.

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.

Abstract: A method of monitoring skin abnormalities on a skin portion of a patient including the steps of receiving a first image data from an image capture device and identifying a first skin mask corresponding to the skin portion. The image data includes the skin portion and a first scaling element on the skin portion. The method further includes the steps of identifying one or more first keypoints within the first skin mask and classifying the one or more keypoints. Each first keypoint comprises an abnormality on the skin portion.

Abstract: A method of monitoring skin abnormalities on a skin portion of a patient including the steps of receiving a first image data from an image capture device and identifying a first skin mask corresponding to the skin portion. The image data includes the skin portion and a first scaling element on the skin portion. The method further includes the steps of identifying one or more first keypoints within the first skin mask and classifying the one or more keypoints. Each first keypoint comprises an abnormality on the skin portion.