Patents by Inventor Sunli Tang

Sunli Tang 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).

  • DEEP LEARNING TECHNIQUES FOR SUPPRESSING ARTEFACTS IN MAGNETIC RESONANCE IMAGES
    Publication number: 20230417852
    Abstract: Techniques for removing artefacts, such as RF interference and/or noise, from magnetic resonance data. The techniques include: obtaining input magnetic resonance (MR) data using at least one radio-frequency (RF) coil of a magnetic resonance imaging (MRI) system; and generating an MR image from input MR data at least in part by using a neural network model to suppress at least one artefact in the input MR data.
    Type: Application
    Filed: September 12, 2023
    Publication date: December 28, 2023
    Applicant: Hyperfine Operations, Inc.
    Inventors: Carole LAZARUS, Prantik KUNDU, Sunli TANG, Seyed Sadegh Mohseni SALEHI, Michal SOFKA, Jo SCHLEMPER, Hadrien A. DYVORNE, Rafael O'HALLORAN, Laura SACOLICK, Michael Stephen POOLE, Jonathan M. ROTHBERG
  • Deep learning techniques for suppressing artefacts in magnetic resonance images
    Patent number: 11789104
    Abstract: Techniques for removing artefacts, such as RF interference and/or noise, from magnetic resonance data. The techniques include: obtaining input magnetic resonance (MR) data using at least one radio-frequency (RF) coil of a magnetic resonance imaging (MRI) system; and generating an MR image from input MR data at least in part by using a neural network model to suppress at least one artefact in the input MR data.
    Type: Grant
    Filed: August 15, 2019
    Date of Patent: October 17, 2023
    Assignee: Hyperfine Operations, Inc.
    Inventors: Carole Lazarus, Prantik Kundu, Sunli Tang, Seyed Sadegh Mohseni Salehi, Michal Sofka, Jo Schlemper, Hadrien A. Dyvorne, Rafael O'Halloran, Laura Sacolick, Michael Stephen Poole, Jonathan M. Rothberg
  • DEEP LEARNING TECHNIQUES FOR SUPPRESSING ARTEFACTS IN MAGNETIC RESONANCE IMAGES
    Publication number: 20200058106
    Abstract: Techniques for removing artefacts, such as RF interference and/or noise, from magnetic resonance data. The techniques include: obtaining input magnetic resonance (MR) data using at least one radio-frequency (RF) coil of a magnetic resonance imaging (MRI) system; and generating an MR image from input MR data at least in part by using a neural network model to suppress at least one artefact in the input MR data.
    Type: Application
    Filed: August 15, 2019
    Publication date: February 20, 2020
    Inventors: Carole Lazarus, Prantik Kundu, Sunli Tang, Seyed Sadegh Moshen Salehi, Michal Sofka, Jo Schlemper, Hadrien A. Dyvorne, Rafael O'Halloran, Laura Sacolick, Michael Stephen Poole, Jonathan M. Rothberg