Patents by Inventor Florent Billy Romaric Gbelidji

Florent Billy Romaric Gbelidji 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: 10810767
    Abstract: For low-complexity to learned reconstruction and/or learned Fourier transform-based operators for reconstruction, a neural network is used for the transform operators. The network architecture is modeled on the Cooley-Tukey fast Fourier transform (FFT) approach. By splitting input data before recursive calls in the network architecture, the network may be trained to perform the transform with similar complexity as FFT. The learned operators may be used in a trained network for reconstruction, such as with a learned iterative framework and image regularizer.
    Type: Grant
    Filed: October 3, 2018
    Date of Patent: October 20, 2020
    Assignee: Siemens Healthcare GmbH
    Inventors: Boris Mailhe, Simon Arberet, Florent Billy Romaric Gbelidji, Mariappan S. Nadar
  • Publication number: 20190378311
    Abstract: For low-complexity to learned reconstruction and/or learned Fourier transform-based operators for reconstruction, a neural network is used for the transform operators. The network architecture is modeled on the Cooley-Tukey fast Fourier transform (FFT) approach. By splitting input data before recursive calls in the network architecture, the network may be trained to perform the transform with similar complexity as FFT. The learned operators may be used in a trained network for reconstruction, such as with a learned iterative framework and image regularizer.
    Type: Application
    Filed: October 3, 2018
    Publication date: December 12, 2019
    Inventors: Boris Mailhe, Simon Arberet, Florent Billy Romaric Gbelidji, Mariappan S. Nadar