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Publication Detail
Spatio-Temporal Deep De-aliasing for Assessment of Ventricular Volumes Using Real-Time Tiny Golden Angle Radial SSFP; Feasibility in Adults with Congenital Heart Disease
  • Publication Type:
    Conference presentation
  • Publication Sub Type:
    Presentation
  • Authors:
    Steeden J, Hauptmann A, Muthurangu V, Arridge S
  • Date:
    14/03/2018
  • Name of Conference:
    ISMRM Workshop on Machine Learning
  • Conference place:
    Asilomar Conference Grounds, Pacific Grove, CA, USA
Abstract
Real-time MR techniques allow rapid acquisition of ventricular volumes during free-breathing and without cardiac gating. However, high acceleration factors are required to ensure adequate spatial and temporal resolution imaging. Compressed sensing (CS) is the gold standard reconstruction technique for accelerated real-time acquisitions. The problem with CS is that it is time consuming and can lead to unnatural looking images. The purpose of this study is to investigate deep learning algorithms for reconstruction of real-time volumetric MR data, to allow improved reconstruction speed and/or improved image quality compared to CS.
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Dept of Computer Science
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Dept of Computer Science
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Childrens Cardiovascular Disease
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Childrens Cardiovascular Disease
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