Keywords
Parallel Imaging Technique
K-Space
Incoherent Subsampling
Transform Sparsity
Non-Linear Iterative Reconstruction
Aliasing Artifact
Phased Array Coil
How to Cite
Abstract
This Project Work intends to illustrate the technique of Compressed Sense (CS), innovative method introduced in the
field of signal processing, which allows you to capture signals and images with far fewer samplings than “needed”,
reducing scan times up to 50% and offering accurate and high resolution images.
The Compressed Sense technique can be successfully applied for Imaging in Magnetic Resonance as it satisfies the
properties of sparsity and incoherent. One of the primary requirements of the CS is based on the use of particular
mathematical bases, whose function will be to represent the sampled functions. Between these, the Wavelet bases
are of considerable importance as they subdivide the data in question into components of different frequencies, and
therefore allow to study every component of the frequency spectrum with a resolution matched to its scale, such as,
for example, those that are used in the encoding of images with the JPEG-2000. The Compressed Sense technique has
allowed us to overcome the intrinsic physical limits inherent in the matter, developing a technique that continues to
evolve and expand, improving and refining.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright (c) 2023 Journal of Advanced Health Care
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