Patents by Inventor Ranjeeta Thapa

Ranjeeta Thapa 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).

  • Publication number: 20240325785
    Abstract: Systems and methods for accelerated online adaptive radiation therapy (“ART”) are described. The improvements to online ART are generally provided based on the use of textural analysis and machine learning algorithms implemented with a hardware processor and a memory. The described systems and methods enable more efficient and accurate online adaptive replanning (“OLAR”), which can also be implemented in clinically acceptable timeframes. For example, OLAR can be reduced from taking 10-30 minutes down to 5-10 minutes.
    Type: Application
    Filed: June 7, 2024
    Publication date: October 3, 2024
    Inventors: X. Allen Li, Ying Zhang, Sara Lim, Jingqiao Zhang, Ergun Ahunbay, Ranjeeta Thapa, Haidy Nasief
  • Patent number: 12005270
    Abstract: Systems and methods for accelerated online adaptive radiation therapy (“ART”) are described. The improvements to online ART are generally provided based on the use of textural analysis and machine learning algorithms implemented with a hardware processor and a memory. The described systems and methods enable more efficient and accurate online adaptive replanning (“OLAR”), which can also be implemented in clinically acceptable timeframes. For example, OLAR can be reduced from taking 10-30 minutes down to 5-10 minutes.
    Type: Grant
    Filed: June 26, 2019
    Date of Patent: June 11, 2024
    Assignee: The Medical College of Wisconsin, Inc.
    Inventors: X. Allen Li, Ying Zhang, Sara Lim, Jingqiao Zhang, Ergun Ahunbay, Ranjeeta Thapa, Haidy Nasief
  • Publication number: 20210220670
    Abstract: Systems and methods for accelerated online adaptive radiation therapy (“ART”) are described. The improvements to online ART are generally provided based on the use of textural analysis and machine learning algorithms implemented with a hardware processor and a memory. The described systems and methods enable more efficient and accurate online adaptive replanning (“OLAR”), which can also be implemented in clinically acceptable timeframes. For example, OLAR can be reduced from taking 10-30 minutes down to 5-10 minutes.
    Type: Application
    Filed: June 26, 2019
    Publication date: July 22, 2021
    Inventors: X. Allen Li, Ying Zhang, Sara Lim, Jingqiao Zhang, Ergun Ahunbay, Ranjeeta Thapa, Haidy Nasief