NetForum uses cookies to ensure that we give you the best experience on our website. If you continue to use the site, we'll assume that you are happy to receive these cookies on the NetForum website. Read about our cookies.
NetForum Community
Learn. Share. Optimize.
Log in | Sign up now | Submit content | Contact

Attention valued NetForum members:

Due to evolving technology needs and global privacy regulations, we have made the hard decision to suspend the NetForum User Community platform on Friday, November 29, 2019.

After this date, the current NetForum can no longer be reached. Please click here for more information about this decision, what happens next and how to stay in touch with us about the future of the community.

Go to similar content

Understanding how Compressed SENSE makes MRI faster

White Paper
Haselhoff, Eltjo, Ph.D. Philps Healthcare • Netherlands

Compressed SENSE is the latest Philips MRI acceleration method, based on our industry leading dStream architecture. Compressed SENSE further expands the performance of dS SENSE, making MRI scans up to an additional 50% faster*, with virtually identical image quality. Alternatively, Compressed SENSE can increase the image resolution up to 40% within the same scan time. Compressed SENSE can be applied to all anatomies and works for both 3D as well as for 2D MRI acquisitions, making it a powerful asset for almost all clinical MRI exams.

Compressed sensing vs other acceleration methods

Compressed sensing is a term from the field of digital signal processing. When a signal is digitally sampled, like it happens in an MRI scanner, the signal is not recorded continuously (like old cassette players used to do) but at intervals. A famous theorem from digital signal analysis, the Nyquist theorem, states that for constructing a perfect MR image of 256 x 256 pixels, it is required to sample 256 lines in k-space, each sampled in 256 positions. By doing less, the acquisition will be faster, but the reconstructed image will always be distorted one way or another.

This is exactly what happens with traditional acceleration techniques in MRI, such as halfscan, radial, spiral, increased voxel size and parallel imaging. All of these methods skip parts of k-space during acquisition in order to reduce acquisition time. However, there will always be a penalty: either a reduced signal-to-noise ratio (halfscan, parallel imaging), lower image resolution (increased voxel size) or image artifacts (spiral, radial).

Compressed sensing is not different, but in practice it is often more forgiving than other acceleration techniques in terms of image distortion and SNR, because it can be designed to primarily sample the MR signals that matter most, while leaving out the rest. A unique aspect about compressed sensing is that it can bypass the aforementioned Nyquist theorem: although not enough samples are taken for perfect image reconstruction, a good compressed sensing reconstruction can successfully remove the inherent artifacts and produce excellent diagnostic images.

Philips Compressed SENSE for faster MRI without sacrificing image quality*

Compressed SENSE is the Philips implementation of the compressed sensing principle. It combines dS SENSE, our industry leading parallel imaging method, with compressed sensing. As a result, it can reduce the scan times by up to 50% compared to current examinations without Compressed SENSE.

Philips Compressed SENSE is unique for various reasons:

• Compressed sensing reconstructions can be done in many different ways. Our algorithm uses a priori information from system calibration data, anatomical knowledge and general MRI principles. All of this information is carefully balanced to reconstruct the best possible MRI image quality, whilst keeping it consistent with the measured MRI data.

• Traditionally, the time gained with a compressed sensing acquisition is lost again during image reconstruction, which is typically very long, and requires careful parameter optimization by the user. Not so for Compressed SENSE, which typically reconstructs under a minute, without the need for complex user interactions, nor dedicated reconstruction hardware. This pulls it out of the research realm straight into clinical practice.

• Thanks to our unique dS SENSE infrastructure we have full k-space sampling flexibility for our compressed sensing algorithms. This means that Compressed SENSE, unlike other solutions on the market, has the full freedom to optimize k-space sampling for excellent SNR and sharpness, without any restrictions whatsoever.

• As a result of this flexibility, Philips Compressed SENSE can be applied to both 3D and 2D MRI acquisitions, making it applicable to most clinical routine MRI scans.

The Compressed SENSE principle in pictures

In the example below, only one fifth of the required MR radiofrequency
signals is recorded. This results in a five times faster acquisition, with a
subsampled k-space (top left) and inherent image artifacts after
standard reconstruction (top right).

Basic compressed sensing principle

 k-space image
k-space
image

Philips Compressed SENSE

 k-space
<br><br> image
k-space

image
The Compressed SENSE reconstruction then uses iterative, knowledge-based
algorithms to fill in the empty lines in k-space (bottom left). This removes
the artifacts while keeping the final image fully consistent with the acquired
data (bottom right).


Compressed SENSE can be used in all anatomical contrasts, enabling scans
to be up to 50% faster with virtually equal image quality*



*Compared to Philips MR exams without Compressed SENSE


This content has been made possible by NetForum Community.
Share this on: Share your link in twitter Share your link in facebook Share your link on LinkedIn Print Rate this article: Log in to vote

 
Rating:
Votes:
2
Views:
382
Added:
Oct 21, 2019

Rate this:
Log in to vote
 

White Paper
Achieva 1.5T dStream, Achieva 3.0T dStream, Ambition, Elition, Ingenia 1.5T, Ingenia 3.0T
Body, Cardiac, Compressed SENSE, compressed sensing, dS SENSE, Musculoskeletal, Neuro, Vascular
 

Clinical News
Best Practices
Case Studies
Publications and Abstracts
White Papers
Web seminars and Presentations
ExamCards
Protocols
Application Tips and FAQ
Training
Try an Application
Business News
Case Studies
White Papers
Web Seminars and Presentations
Utilization Services
Contributing Professionals
Contributing Institutions
Become a Contributor