Patents by Inventor Najib Akram

Najib Akram 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: 11615508
    Abstract: A method for automatic selection of display settings for a medical image is provided. The method includes receiving a medical image, mapping the medical image to an appearance classification cell of an appearance classification matrix using a trained deep neural network, selecting a first WW and a first WC for the medical image based on the appearance classification and a target appearance classification, adjusting the first WW and the first WC based on user preferences to produce a second WW and a second WC, and displaying the medical image with the second WW and the second WC via a display device.
    Type: Grant
    Filed: February 7, 2020
    Date of Patent: March 28, 2023
    Assignee: GE Precision Healthcare LLC
    Inventors: German Guillermo Vera-Gonzalez, Najib Akram, Ping Xue, Fengchao Zhang, Gireesha Chinthamani Rao, Justin Wanek
  • Patent number: 11564651
    Abstract: Various methods and systems are provided for x-ray imaging. In one embodiment, a method for an image pasting examination comprises acquiring, via an optical camera and/or depth camera, image data of a subject, controlling an x-ray source and an x-ray detector according to the image data to acquire a plurality of x-ray images of the subject, and stitching the plurality of x-ray images into a single x-ray image. In this way, optimal exposure techniques may be used for individual acquisitions in an image pasting examination such that the optimal dose is utilized, stitching quality is improved, and registration failures are avoided.
    Type: Grant
    Filed: January 14, 2020
    Date of Patent: January 31, 2023
    Assignee: GE Precision Healthcare LLC
    Inventors: Dejun Wang, Jingyi Yang, Yaan Ge, Aizhen Zhou, Katelyn Nye, Gireesha Rao, Buer Qi, Najib Akram
  • Publication number: 20210248716
    Abstract: The current disclosure provides systems and methods for intelligent selection of display settings, including window-width (WW) and window-center (WC), for medical images, using deep neural networks. The current disclosure may enable automatic selection of display settings for a medical image, based on a deep neural network's appearance classification of the medical image. In one embodiment, the current disclosure provides a method comprising, receiving a medical image, mapping the medical image to an appearance classification cell of an appearance classification matrix using a trained deep neural network, selecting a first WW and a first WC for the medical image based on the appearance classification and a target appearance classification, adjusting the first WW and the first WC based on user preferences to produce a second WW and a second WC, and displaying the medical image with the second WW and the second WC via a display device.
    Type: Application
    Filed: February 7, 2020
    Publication date: August 12, 2021
    Inventors: German Guillermo Vera-Gonzalez, Najib Akram, Ping Xue, Fengchao Zhang, Gireesha Chinthamani Rao, Justin Wanek
  • Publication number: 20210212650
    Abstract: Various methods and systems are provided for x-ray imaging. In one embodiment, a method for an image pasting examination comprises acquiring, via an optical camera and/or depth camera, image data of a subject, controlling an x-ray source and an x-ray detector according to the image data to acquire a plurality of x-ray images of the subject, and stitching the plurality of x-ray images into a single x-ray image. In this way, optimal exposure techniques may be used for individual acquisitions in an image pasting examination such that the optimal dose is utilized, stitching quality is improved, and registration failures are avoided.
    Type: Application
    Filed: January 14, 2020
    Publication date: July 15, 2021
    Inventors: Dejun Wang, Jingyi Yang, Yaan Ge, Aizhen Zhou, Katelyn Nye, Gireesha Rao, Buer Qi, Najib Akram