Deep learning techniques for suppressing artefacts in magnetic resonance images

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...

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Bibliographic Details
Main Authors KUNDU, PRANTIK, MOSHEN SALEHI, SEYED SADEGH, SACOLICK, LAURA, O'HALLORAN, RAFAEL, TANG, SUN-LI, SOFKA, MICHAL, POOLE, MICHAEL STEPHEN, ROTHBERG, JONATHAN M, DYVORNE, HADRIEN A, LAZARUS, CAROLE, SCHLEMPER, JO
Format Patent
LanguageChinese
English
Published 16.07.2020
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
DIAGNOSIS
HUMAN NECESSITIES
HYGIENE
IDENTIFICATION
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
MEDICAL OR VETERINARY SCIENCE
PHYSICS
SURGERY
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Summary: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.
Bibliography:Application Number: TW20198129138