Patents by Inventor Tomi RUOKOLA

Tomi RUOKOLA 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: 12223660
    Abstract: Systems and methods for anatomical structure segmentation in medical images using multiple anatomical structures, instructions and segmentation models.
    Type: Grant
    Filed: September 14, 2023
    Date of Patent: February 11, 2025
    Assignee: SIEMENS HEALTHINEERS INTERNATIONAL AG
    Inventors: Hannu Mikael Laaksonen, Janne Nord, Maria Isabel Cordero Marcos, Sami Petri Perttu, Tomi Ruokola
  • Publication number: 20240005515
    Abstract: Systems and methods for anatomical structure segmentation in medical images using multiple anatomical structures, instructions and segmentation models.
    Type: Application
    Filed: September 14, 2023
    Publication date: January 4, 2024
    Inventors: Hannu Mikael LAAKSONEN, Janne NORD, Maria Isabel CORDERO MARCOS, Sami Petri PERTTU, Tomi RUOKOLA
  • Patent number: 11842498
    Abstract: Systems and methods for anatomical structure segmentation in medical images using multiple anatomical structures, instructions and segmentation models.
    Type: Grant
    Filed: December 16, 2019
    Date of Patent: December 12, 2023
    Assignee: SIEMENS HEALTHINEERS INTERNATIONAL AG
    Inventors: Hannu Mikael Laaksonen, Janne Nord, Maria Isabel Cordero Marcos, Sami Petri Perttu, Tomi Ruokola
  • Publication number: 20220051781
    Abstract: Example methods and systems for deep transfer learning for radiotherapy treatment planning are provided. One example method may comprise: obtaining (310) a base deep learning engine that is pre-trained to perform a base radiotherapy treatment planning task; and based on the base deep learning engine, generating a target deep learning engine to perform a target radiotherapy treatment planning task. The target deep learning engine may be generated by configuring (330) a variable base layer among multiple base layers of the base deep learning engine, and generating (340) one of multiple target layers of the target deep learning engine by modifying the variable base layer. Alternatively or additionally, the target deep learning engine may be generated by configuring (350) an invariable base layer among the multiple base layers, and generating (360) one of multiple target layers of the target deep learning engine based on feature data generated using the invariable base layer.
    Type: Application
    Filed: May 30, 2019
    Publication date: February 17, 2022
    Applicant: VARIAN MEDICAL SYSTEMS INTERNATIONAL AG
    Inventors: Hannu Mikael LAAKSONEN, Sami Petri PERTTU, Tomi RUOKOLA, Jan SCHREIER, Janne NORD
  • Publication number: 20210183070
    Abstract: Systems and methods for anatomical structure segmentation in medical images using multiple anatomical structures, instructions and segmentation models.
    Type: Application
    Filed: December 16, 2019
    Publication date: June 17, 2021
    Inventors: Hannu Mikael LAAKSONEN, Janne NORD, Maria Isabel CORDERO MARCOS, Sami Petri PERTTU, Tomi RUOKOLA