Compressed Sensing
Articles and keynotes
Get beyond the barrier of acquisition speed
Compressed Sensing (CS) is an exciting new method with the potential to accelerate MR imaging beyond what is possible with any other method. The successful utilization of Compressed Sensing is a team play of data acquisition and image reconstruction. Read the articles below to learn how it works.
Christoph Forman explains the three golden rules of Compressed Sensing
Watch the video and learn how the technology works.
Compressed Sensing: a Paradigm Shift in MRI
Christoph Forman et al.
Compressed Sensing: the Flowchart
Mathias Blasche et al.
Compressed Sensing: a Metaphor
Mathias Blasche
The Rapid Imaging Renaissance
Daniel K. Sodickson, Ph.D., M.D., New York University Langone Medical Center, New York, USA
CS in Cardiovascular MRI
Highly Accelerated 4D Flow Imaging using Compressed Sensing – a Comparison with Conventional 4D Flow in Healthy Volunteers and Patients with Aortic Diseases
Tilman Emrich, M.D.; et al.
University Medical Center Mainz, Germany
Performance of Compressed Sensing Cardiac Cine Imaging in Children: Initial Experience
Aurelio Secinaro, et al., Bambino Gesù Children’s Hospital, Rome, Italy
Adding Value in CMRI with MAGNETOM Sola's BioMatrix Technology
Johan Dehem, M.D., VZW Jan Yperman, Ypres, Belgium
Impact of Compressed Sensing Cardiac Cine in a busy clinical practice
Jérome Garot, M.D., Ph.D., et al., Institut Cardiovasculaire Paris Sud, Massy, France
Compressed Sensing
Matthias Stuber, Dept. of Radiology, CHUV, Lausanne, Switzerland
How to improve time efficiency in Cardiac MRI: Clinical experience with compressed sensing
François Pontana, Dept. of Cardiovascular Radiology, Heart and Lung Institute, Lille University Hospital, France
Exercise Cardiac MRI, a Clinical Reality with Compressed Sensing
Wendy Strugnell et al., The Prince Charles Hospital, Chermside, QLD, Australia
Accelerated Segmented Cine TrueFISP of the Heart on a 1.5T MAGNETOM Aera Using k-t-sparse SENSE
Maria Carr et al., Northwestern University, Feinberg School of Medicine, Chicago, IL, USA
Preliminary Experiences with Compressed Sensing Multi-Slice Cine Acquisitions for the Assessment of Left Ventricular Function: CV_sparse WIP
Jurg Schwitter et al., CHUV Lausanne
Compressed Sensing: Application to Time-of-Flight MR Angiography
Tomohisa Okada et al., Kyoto University, Kyoto, Japan
Improving Dynamic MR Angiography: Iterative TWIST
Bernd J. Wintersperger et al., University of Toronto, Toronto, Ontario, Canada
CS in Body MRI
Clinical acceleration: from the console
James Hancock, Benson Radiology, North Adelaide, Australia
A single-breath-hold MRCP using CS: A pilot study at 1.5T and 3T
Valérie Laurent, M.D., Ph.D., et al., Department of Radiology, Nancy University Hospital, Vandoeuvre-lès-Nancy, France
Benefits of Accelerated MRI in Daily Routine
Val M. Runge, M.D. et al., Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, University Hospital, University of Bern, Bern, Switzerland
CS-VIBE – a breakthrough in Ultrafast Dynamic Breast MRI
Ritse M. Mann and Suzan Vreemann, Radboud University Medical Centre, Department of Radiology, Nijmegen, the Netherlands
GRASP: Tackling the Challenges of Abdominopelvic DCE-MRI
Kai Tobias Block et al., NYU Langone Medical Center, New York, NY, USA
Case Report: Detection of Insulinomas with High Spatiotemporal Resolution Using Compressed Sensing, Parallel Imaging, and Continuous Golden-Angle Radial Sampling
Kwadwo Antwi et al., University Hospital Basel, Switzerland
Permeability Imaging of Parotid Tumors with Golden-Angle Radial Sparse Parallel MR Imaging (GRASP)
Sohil H. Patel et al., Department of Radiology, NYU Langone Medical Centre, New York, NY, USA
Free-breathing DCE-MRI of the Kidney using GRASP
Philipp Riffel et al., University Medical Center Mannheim, Germany
CS in Musculoskeletal MRI
Compressed Sensing SEMAC
The CS-SEMAC technique is facilitated by the inherent sparsity of the acquired SEMAC data, since the actual distortions make up for just a small fraction of the acquired signal. Compressed Sensing SEMAC applies 8-fold undersampling of k-space in combination with an iterative reconstruction algorithm. As a result, images with very comparable diagnostic quality can be created from e.g. a six minute CS-SEMAC scan that would otherwise take approximately twelve minutes even with parallel imaging acceleration.
MR Imaging of Joint Replacements
Reto Sutter, M.D. et al., Balgrist University Hospital, University of Zurich, Zurich, Switzerland
MR Imaging of Joint Replacements
Reto Sutter, M.D., Balgrist University Hospital, University of Zurich, Zurich, Switzerland
CS-MRF
Novelties in MR Fingerprinting1
Gregor Körzdörfer, Siemens Healthineers, Erlangen, Germany
1The product/feature is not commercially available in some countries. Due to regulatory reasons its future availability cannot be guaranteed.