Patents by Inventor Tarjei Sveinsgjerd HVEEM

Tarjei Sveinsgjerd HVEEM 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).

  • Patent number: 11989882
    Abstract: A machine learning algorithm is trained on a number of microscopic images and a measure of outcome of each image. Each image is divided into tiles. The measure of outcome is assigned to each tile of the image. The tiles are then used to train the machine learning algorithm. The trained algorithm may then be used to evaluate images.
    Type: Grant
    Filed: May 13, 2022
    Date of Patent: May 21, 2024
    Assignee: OSLO UNIVERSITETSSYKEHUS
    Inventors: Ole Johan Skrede, Tarjei Sveinsgjerd Hveem, John Robert Maddison, Havard Emil Greger Danielsen, Knut Liestol
  • Publication number: 20240037747
    Abstract: A computer implemented system for determining an overall-classifier for one or more source-histological-images. The system comprising: a first tile generator (204) configured to generate a plurality of first-tiles (206; 306) from the one or more source-histological-image (202; 302); and a second tile generator (205) configured to generate a plurality of second-tiles (207; 307) from the one or more source-histological-images (202; 302). The first-area of the first-tiles (206; 306) is larger than the second-area of the second-tiles (207; 307); and the second-resolution of the second-tiles (207; 307) is higher than the first-resolution of the first-tiles (206; 306).
    Type: Application
    Filed: September 18, 2020
    Publication date: February 1, 2024
    Inventors: Sepp De RAEDT, Ole-Johan SKREDE, Håvard Emil Greger DANIELSEN, Tarjei Sveinsgjerd HVEEM, Andreas KLEPPE, Knut LIESTØL
  • Publication number: 20220270258
    Abstract: A machine learning algorithm is trained on a number of microscopic images and a measure of outcome of each image. Each image is divided into tiles. The measure of outcome is assigned to each tile of the image. The tiles are then used to train the machine learning algorithm. The trained algorithm may then be used to evaluate images.
    Type: Application
    Filed: May 13, 2022
    Publication date: August 25, 2022
    Inventors: Ole Johan SKREDE, Tarjei Sveinsgjerd HVEEM, John Robert MADDISON, Havard Emil Greger DANIELSEN, Knut LIESTOL
  • Patent number: 11361442
    Abstract: A machine learning algorithm is trained on a number of microscopic images and a measure of outcome of each image. Each image is divided into tiles. The measure of outcome is assigned to each tile of the image. The tiles are then used to train the machine learning algorithm. The trained algorithm may then be used to evaluate images.
    Type: Grant
    Filed: November 9, 2018
    Date of Patent: June 14, 2022
    Assignee: OSLO UNIVERSITETSSYKEHUS
    Inventors: Ole Johan Skrede, Tarjei Sveinsgjerd Hveem, John Robert Maddison, Havard Emil Greger Danielsen, Knut Liestol
  • Publication number: 20200388036
    Abstract: A machine learning algorithm is trained on a number of microscopic images and a measure of outcome of each image. Each image is divided into tiles. The measure of outcome is assigned to each tile of the image. The tiles are then used to train the machine learning algorithm. The trained algorithm may then be used to evaluate images.
    Type: Application
    Filed: November 9, 2018
    Publication date: December 10, 2020
    Inventors: Ole Johan SKREDE, Tarjei Sveinsgjerd HVEEM, John Robert MADDISON, Havard Emil Greger DANIELSEN, Knut LIESTOL
  • Patent number: 10482314
    Abstract: A method of image classification is used for classifying images of stained cell nuclei. For each nucleus, the total integrated optical density is calculated and a histogram calculated. The image is then classified by automatically identifying peaks, identifying the lowest peak as a 2C peak and classifying the image as at least one of diploid, tetraploid, aneuploid or polyploid based on the number of peaks and the count at an integrated optical densities above the 2C peak.
    Type: Grant
    Filed: March 27, 2018
    Date of Patent: November 19, 2019
    Assignee: OSLO UNIVERSITETSSYKEHUS, INSTITUTE FOR CANCER GENETICS AND INFORMATICS
    Inventors: Rolf Anders Syvertsen, Tarjei Sveinsgjerd Hveem, John Robert Maddison, Havard Emil Greger Danielsen
  • Publication number: 20180293427
    Abstract: A method of image classification is used for classifying images of stained cell nuclei. For each nucleus, the total integrated optical density is calculated and a histogram calculated. The image is then classified by automatically identifying peaks, identifying the lowest peak as a 2C peak and classifying the image as at least one of diploid, tetraploid, aneuploid or polyploid based on the number of peaks and the count at an integrated optical densities above the 2C peak.
    Type: Application
    Filed: March 27, 2018
    Publication date: October 11, 2018
    Inventors: Rolf Anders SYVERTSEN, Tarjei Sveinsgjerd HVEEM, John Robert MADDISON, Havard Emil Greger DANIELSEN