Patents by Inventor Adel S. Elmaghraby

Adel S. Elmaghraby has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Method and system for monitoring and evaluation of pressure ulcer severity
    Patent number: 11234635
    Abstract: Evaluating a pressure ulcer includes: detecting in a color input image a boundary of the pressure ulcer to get a RGB region of interest (ROI) image; converting the RGB ROI image to a grayscale ROI image; processing the grayscale ROI image using a Linear Combination of Discrete Gaussians (LCDG) process to estimate three main class probabilities of the grayscale ROI image; processing the RGB ROI image using predetermined RGB values to estimate the three main class probabilities of the RGB ROI image; and combining the probabilities of the grayscale ROI image and the probabilities of the RGB ROI image to determine an estimated labeled image; and normalizing and refining the estimated labeled image using a Generalized Gauss-Markov Random Field (GGMRF) process to produce a final segmentation image.
    Type: Grant
    Filed: May 18, 2018
    Date of Patent: February 1, 2022
    Assignees: University of Louisville Research Foundation, Inc, Fundacion Deusto, Universidad de Deusto
    Inventors: Adel S. Elmaghraby, Maria Begoña García-Zapirain Soto, Ayman Sabry El-Baz
  • METHOD AND SYSTEM FOR MONITORING AND EVALUATION OF PRESSURE ULCER SEVERITY
    Publication number: 20210106274
    Abstract: Evaluating a pressure ulcer includes: detecting in a color input image a boundary of the pressure ulcer to get a RGB region of interest (ROI) image; converting the RGB ROI image to a grayscale ROI image; processing the grayscale ROI image using a Linear Combination of Discrete Gaussians (LCDG) process to estimate three main class probabilities of the grayscale ROI image; processing the RGB ROI image using predetermined RGB values to estimate the three main class probabilities of the RGB ROI image; and combining the probabilities of the grayscale ROI image and the probabilities of the RGB ROI image to determine an estimated labeled image; and normalizing and refining the estimated labeled image using a Generalized Gauss-Markov Random Field (GGMRF) process to produce a final segmentation image.
    Type: Application
    Filed: May 18, 2018
    Publication date: April 15, 2021
    Applicant: University of Louisville Research Foundation, Inc.
    Inventors: Adel S. Elmaghraby, Maria Begoña García-Zapirain Soto, Ayman Sabry El-Baz