Patents by Inventor Itzhak LEICHTER

Itzhak LEICHTER 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).

  • Machine learning detection and classification of maxillofacial bone lesions in CBCT
    Patent number: 11853855
    Abstract: A computer-implemented method comprising: receiving a plurality of CBCT scans, each comprising a series of axial slices, wherein the CBCT scans are associated with a cohort of subjects comprising a first subgroup of subjects having each one or more maxillofacial bone lesions, and a second subgroup of subjects having no maxillofacial bone lesions; applying a feature extraction operation to extract a set of features from the axial slices in each of the CBCT scans; at a training stage, training a machine learning model on a training dataset comprising: (i) all of the extracted sets of features, and (ii) annotations indicating boundaries of bone lesions in the axial slices, to obtain a trained machine learning model configured to detect and segment a bone lesion in an axial slice from a CBCT scan.
    Type: Grant
    Filed: May 4, 2023
    Date of Patent: December 26, 2023
    Assignees: HADASIT MEDICAL RESEARCH SERVICES & DEVELOPMENT LTD., JERUSALEM COLLEGE OF TECHNOLOGY
    Inventors: Chen Nadler, Ragda Abdalla Aslan, Talia Yeshua, Itzhak Leichter
  • MACHINE LEARNING DETECTION AND CLASSIFICATION OF MAXILLOFACIAL BONE LESIONS IN CBCT
    Publication number: 20230359936
    Abstract: A computer-implemented method comprising: receiving a plurality of CBCT scans, each comprising a series of axial slices, wherein the CBCT scans are associated with a cohort of subjects comprising a first subgroup of subjects having each one or more maxillofacial bone lesions, and a second subgroup of subjects having no maxillofacial bone lesions; applying a feature extraction operation to extract a set of features from the axial slices in each of the CBCT scans; at a training stage, training a machine learning model on a training dataset comprising: (i) all of the extracted sets of features, and (ii) annotations indicating boundaries of bone lesions in the axial slices, to obtain a trained machine learning model configured to detect and segment a bone lesion in an axial slice from a CBCT scan.
    Type: Application
    Filed: May 4, 2023
    Publication date: November 9, 2023
    Inventors: Chen NADLER, Ragda Abdalla ASLAN, Talia YESHUA, Itzhak LEICHTER