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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Main Authors | , , , , , , , , , , |
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Format | Patent |
Language | Chinese English |
Published |
16.07.2020
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Subjects | |
Online Access | Get full text |
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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. |
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AbstractList | 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. |
Author | MOSHEN SALEHI, SEYED SADEGH KUNDU, PRANTIK LAZARUS, CAROLE DYVORNE, HADRIEN A SCHLEMPER, JO ROTHBERG, JONATHAN M O'HALLORAN, RAFAEL POOLE, MICHAEL STEPHEN TANG, SUN-LI SOFKA, MICHAL SACOLICK, LAURA |
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Snippet | Techniques for removing artefacts, such as RF interference and/or noise, from magnetic resonance data. The techniques include: obtaining input magnetic... |
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Title | Deep learning techniques for suppressing artefacts in magnetic resonance images |
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