Sparse reconstruction techniques in magnetic resonance imaging: methods, applications, and challenges to clinical adoption

The family of sparse reconstruction techniques, including the recently introduced compressed sensing framework, has been extensively explored to reduce scan times in magnetic resonance imaging (MRI). While there are many different methods that fall under the general umbrella of sparse reconstruction...

Full description

Saved in:
Bibliographic Details
Main Authors: Yang, Alice C. (Author) , Janssen, Sonja (Author)
Format: Article (Journal)
Language:English
Published: June 2016
In: Investigative radiology
Year: 2016, Volume: 51, Issue: 6, Pages: 349-364
ISSN:1536-0210
DOI:10.1097/RLI.0000000000000274
Online Access:Verlag, Volltext: https://doi.org/10.1097/RLI.0000000000000274
Verlag, Volltext: http://content.wkhealth.com/linkback/openurl?sid=WKPTLP:landingpage&an=00004424-201606000-00001
Get full text
Author Notes:Alice C. Yang, BS, Madison Kretzler, MS, Sonja Sudarski, MD, Vikas Gulani, MD, PhD, and Nicole Seiberlich, PhD
Description
Summary:The family of sparse reconstruction techniques, including the recently introduced compressed sensing framework, has been extensively explored to reduce scan times in magnetic resonance imaging (MRI). While there are many different methods that fall under the general umbrella of sparse reconstructions, they all rely on the idea that a priori information about the sparsity of MR images can be used to reconstruct full images from undersampled data. This review describes the basic ideas behind sparse reconstruction techniques, how they could be applied to improve MRI, and the open challenges to their general adoption in a clinical setting. The fundamental principles underlying different classes of sparse reconstructions techniques are examined, and the requirements that each make on the undersampled data outlined. Applications that could potentially benefit from the accelerations that sparse reconstructions could provide are described, and clinical studies using sparse reconstructions reviewed. Lastly, technical and clinical challenges to widespread implementation of sparse reconstruction techniques, including optimization, reconstruction times, artifact appearance, and comparison with current gold standards, are discussed.
Item Description:Gesehen am 01.07.2019
Physical Description:Online Resource
ISSN:1536-0210
DOI:10.1097/RLI.0000000000000274