DEEP LEARNING TECHNIQUES FOR SUPPRESSING ARTEFACTS IN MAGNETIC RESONANCE IMAGES

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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Bibliographische Detailangaben
Hauptverfasser: Lazarus, Carole, Sacolick, Laura, Poole, Michael Stephen, Rothberg, Jonathan M, Schlemper, Jo, Dyvorne, Hadrien A, O'Halloran, Rafael, Sofka, Michal, Kundu, Prantik, Moshen Salehi, Seyed Sadegh, Tang, Sunli
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
PHYSICS
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Beschreibung
Zusammenfassung: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.