Patents by Inventor Julio A. Oscanoa Aida

Julio A. Oscanoa Aida 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).

  • Artificial intelligence based reconstruction for phase contrast magnetic resonance imaging
    Patent number: 11550014
    Abstract: A method for phase-contrast magnetic resonance imaging (PC-MRI) acquires undersampled PC-MRI data using a magnetic resonance imaging scanner and reconstructs MRI images from the undersampled PC-MRI data by reconstructing a first flow-encoded image using a first convolutional neural network, reconstructing a complex difference image using a second convolutional neural network, combining the complex difference image and the first flow-encoded image to obtain a second flow-encoded image, and generating a velocity encoded image from the first flow-encoded image and second flow-encoded image using phase difference processing.
    Type: Grant
    Filed: February 16, 2022
    Date of Patent: January 10, 2023
    Assignees: The Board of Trustees of the Leland Stanford Junior University, The United States of America as represented by The Department Of Veterans Affairs
    Inventors: Daniel B. Ennis, Matthew J. Middione, Julio A. Oscanoa Aida, Shreyas S. Vasanawala
  • Randomized dimension reduction for magnetic resonance image iterative reconstruction
    Publication number: 20220381863
    Abstract: In a method for magnetic resonance imaging pseudorandomly undersampled k- space imaging data is acquired with multiple receiver coils of an MRI imaging apparatus. MR image reconstruction is performed to produce a reconstructed MR image from the k-space imaging data by iteratively solving sketched approximations of an original reconstruction problem. The sketched approximations use a sketched model matrix As that is a lower-dimensional version of an original model matrix A of the original reconstruction problem. The sketched model matrix As preserves the Fourier structure of the MR reconstruction problem and reduces the number of coils actively used during reconstruction.
    Type: Application
    Filed: May 13, 2022
    Publication date: December 1, 2022
    Inventors: Julio A. Oscanoa Aida, Frank Ong, Mert Pilanci
  • Artificial Intelligence based reconstruction for Phase Contrast Magnetic Resonance Imaging
    Publication number: 20220260660
    Abstract: A method for phase-contrast magnetic resonance imaging (PC-MRI) acquires undersampled PC-MRI data using a magnetic resonance imaging scanner and reconstructs MRI images from the undersampled PC-MRI data by reconstructing a first flow-encoded image using a first convolutional neural network, reconstructing a complex difference image using a second convolutional neural network, combining the complex difference image and the first flow-encoded image to obtain a second flow-encoded image, and generating a velocity encoded image from the first flow-encoded image and second flow-encoded image using phase difference processing.
    Type: Application
    Filed: February 16, 2022
    Publication date: August 18, 2022
    Inventors: Daniel B. Ennis, Matthew J. Middione, Julio A. Oscanoa Aida, Shreyas S. Vasanawala