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US Patent 11300645 Deep learning techniques for magnetic resonance image reconstruction

Patent 11300645 was granted and assigned to Hyperfine on April, 2022 by the United States Patent and Trademark Office.

Overview Structured Data Issues Contributors

Is a

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Patent attributes

Patent Applicant

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Current Assignee

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Patent Jurisdiction

United States Patent and Trademark Office

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Patent Number

Patent Inventor Names

Rafael O'Halloran0

Seyed Sadegh Moshen Salehi0

Ziyi Wang0

Jonathan M. Rothberg0

Laura Sacolick0

Michal Sofka0

Prantik Kundu0

Carole Lazarus0

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Date of Patent

April 12, 2022

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Patent Application Number

165246380

Date Filed

July 29, 2019

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Patent Citations

US Patent 10274563 Magnetic resonance imaging apparatus and method

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US Patent 10520566 Low-field magnetic resonance imaging methods and apparatus

US Patent 10527692 Rotatable magnet methods and apparatus for a magnetic resonance imaging system

US Patent 10534058 Systems and methods for automated detection in magnetic resonance images

US Patent 10534059 Bayesian model for highly accelerated phase-contrast MRI

US Patent 10539637 Portable magnetic resonance imaging methods and apparatus

US Patent 10545207 Low-field magnetic resonance imaging methods and apparatus

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US Patent 10551452 Radio frequency coil tuning methods and apparatus

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Patent Citations Received

US Patent 11681000 Self ensembling techniques for generating magnetic resonance images from spatial frequency data

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US Patent 11789104 Deep learning techniques for suppressing artefacts in magnetic resonance images

US Patent 12105173 Self ensembling techniques for generating magnetic resonance images from spatial frequency data

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US Patent 11564590 Deep learning techniques for generating magnetic resonance images from spatial frequency data

Patent Primary Examiner

Vincent Rudolph

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CPC Code

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G06T 2207/10088

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A magnetic resonance imaging (MRI) system, comprising: a magnetics system comprising: a B

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