Patents by Inventor Arkadiusz GERTYCH

Arkadiusz GERTYCH 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).

  • Predicting DCIS recurrence risk using a machine learning-based high-content image analysis approach
    Patent number: 12175367
    Abstract: Embodiments of the present systems and methods may provide improved capability to predict the risk of recurrence of ductal carcinoma in situ (DCIS) conditions using whole slide image analysis based on machine learning techniques. For example, in an embodiment, a computer-implemented method for determining treatment of a patient may comprise receiving an image of living tissue of a patient, annotating the entire image into tissue structures, extracting texture features from the annotated image, determining a distribution of the extracted texture features relative to tissue conditions, classifying the patient into a risk group based on the distribution, and treating the patient accordingly based on the risk group.
    Type: Grant
    Filed: December 16, 2019
    Date of Patent: December 24, 2024
    Assignee: Georgia State University Research Foundation, Inc.
    Inventors: Sergey Klimov, Yi Jiang, Arkadiusz Gertych
  • Predicting DCIS Recurrence Risk Using a Machine Learning-Based High-Content Image Analysis Approach
    Publication number: 20220058801
    Abstract: Embodiments of the present systems and methods may provide improved capability to predict the risk of recurrence of ductal carcinoma in situ (DCIS) conditions using whole slide image analysis based on machine learning techniques. For example, in an embodiment, a computer-implemented method for determining treatment of a patient may comprise receiving an image of living tissue of a patient, annotating the entire image into tissue structures, extracting texture features from the annotated image, determining a distribution of the extracted texture features relative to tissue conditions, classifying the patient into a risk group based on the distribution, and treating the patient accordingly based on the risk group.
    Type: Application
    Filed: December 16, 2019
    Publication date: February 24, 2022
    Inventors: Sergey Klimov, Yi Jiang, Arkadiusz Gertych
  • Automated delineation of nuclei for three dimensional (3-D) high content screening
    Patent number: 10733417
    Abstract: In various embodiments, the invention teaches systems and methods for analyzing an image of cells, including an image obtained by confocal microscopy, and delineating cell nuclei in the image. In some embodiments, the systems and methods apply a three-dimensional (3-D) radial symmetry transform followed by adaptive post processing of symmetry images to arrive at a mask of seeds that can guide watershed-based segmentation.
    Type: Grant
    Filed: April 22, 2016
    Date of Patent: August 4, 2020
    Assignee: Cedars-Sinai Medical Center
    Inventors: Arkadiusz Gertych, Beatrice Knudsen
  • AUTOMATED DELINEATION OF NUCLEI FOR THREE DIMENSIONAL (3-D) HIGH CONTENT SCREENING
    Publication number: 20180075279
    Abstract: In various embodiments, the invention teaches systems and methods for analyzing an image of cells, including an image obtained by confocal microscopy, and delineating cell nuclei in the image. In some embodiments, the systems and methods apply a three-dimensional (3-D) radial symmetry transform followed by adaptive post processing of symmetry images to arrive at a mask of seeds that can guide watershed-based segmentation.
    Type: Application
    Filed: April 22, 2016
    Publication date: March 15, 2018
    Applicant: Cedars-Sinai Medical Center
    Inventors: Arkadiusz GERTYCH, Beatrice KNUDSEN