Patents by Inventor Ilknur Icke

Ilknur Icke 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: 11030750
    Abstract: Approaches for the automatic segmentation of magnetic resonance (MR) images. Machine learning models segment images to identify image features in consecutive frames at different levels of resolution. A neural network block is applied to groups of MR images to produce primary feature maps at two or more levels of resolution. The images in a given group of MR images may correspond to a cycle and have a temporal order. A second RNN block is applied to the primary feature maps to produce two or more output tensors at corresponding levels of resolution. A segmentation block is applied to the two or more output tensors to produce a probability map for the MR images. The first neural network block may be a convolutional neural network (CNN) block. The second neural network block may be a convolutional long short-term (LSTM) block.
    Type: Grant
    Filed: May 30, 2019
    Date of Patent: June 8, 2021
    Assignees: Merck Sharp & Dohme Corp., MSD International GmbH
    Inventors: Antong Chen, Dongqing Zhang, Ilknur Icke, Belma Dogdas, Sarayu Parimal
  • Patent number: 11010591
    Abstract: A protein crystallization trial is automatically analyzed by capturing images of the protein drops in the trial. A machine-learned model, such as a neural network, is applied to classify the images. The model generates a predicted classification from among a set of possible classifications which includes one or more crystal type classifications and one or more non-crystal type classifications. Users may be notified automatically of newly identified crystals (e.g., drops that are classified as a crystal type). The notification may include a link to a user interface that includes results of the trial.
    Type: Grant
    Filed: February 1, 2019
    Date of Patent: May 18, 2021
    Assignee: Merck Sharp & Dohme Corp.
    Inventors: Soheil Ghafurian, Ilknur Icke, Charles A. Lesburg, Belma Dogdas
  • Publication number: 20200250397
    Abstract: A protein crystallization trial is automatically analyzed by capturing images of the protein drops in the trial. A machine-learned model, such as a neural network, is applied to classify the images. The model generates a predicted classification from among a set of possible classifications which includes one or more crystal type classifications and one or more non-crystal type classifications. Users may be notified automatically of newly identified crystals (e.g., drops that are classified as a crystal type). The notification may include a link to a user interface that includes results of the trial.
    Type: Application
    Filed: February 1, 2019
    Publication date: August 6, 2020
    Inventors: Soheil Ghafurian, Ilknur Icke, Charles A. Lesburg, Belma Dogdas
  • Publication number: 20200111214
    Abstract: Approaches for the automatic segmentation of magnetic resonance (MR) images. Machine learning models segment images to identify image features in consecutive frames at different levels of resolution. A neural network block is applied to groups of MR images to produce primary feature maps at two or more levels of resolution. The images in a given group of MR images may correspond to a cycle and have a temporal order. A second RNN block is applied to the primary feature maps to produce two or more output tensors at corresponding levels of resolution. A segmentation block is applied to the two or more output tensors to produce a probability map for the MR images. The first neural network block may be a convolutional neural network (CNN) block. The second neural network block may be a convolutional long short-term (LSTM) block.
    Type: Application
    Filed: May 30, 2019
    Publication date: April 9, 2020
    Inventors: Antong Chen, Dongqing Zhang, Ilknur Icke, Belma Dogdas, Sarayu Parimal
  • Publication number: 20150248478
    Abstract: A computer system and method for maintaining and using a domain ontology. The computer system includes a triple store comprising a domain ontology, a computer-readable tangible medium comprising software instructions, and a processor configured to access the computer-readable tangible medium to load and execute the software instructions. The software instructions provide a write service configured for receiving a request from a client interface of an authenticated user to edit the domain ontology of the triple store and an interface for updating the domain ontology based on the received request. The method includes steps of providing access to a domain ontology stored on a triple store, receiving a request from a client interface of a first client computer an authenticated user to edit the domain ontology of the triple store, and updating the domain ontology based on the received request by storing updates to the domain ontology in the triple store.
    Type: Application
    Filed: February 27, 2015
    Publication date: September 3, 2015
    Inventors: André SKUPIN, Brandon S. Plewe, Sean Ahearn, Ilknur Icke