Interpolated Compressed Sensing for 2D Multiple Slice Fast MR Imaging
نویسندگان
چکیده
منابع مشابه
Interpolated Compressed Sensing for 2D Multiple Slice Fast MR Imaging
Sparse MRI has been introduced to reduce the acquisition time and raw data size by undersampling the k-space data. However, the image quality, particularly the contrast to noise ratio (CNR), decreases with the undersampling rate. In this work, we proposed an interpolated Compressed Sensing (iCS) method to further enhance the imaging speed or reduce data size without significant sacrifice of ima...
متن کاملAutomatic quality assessment for multi-slice 2D FLAIR MR imaging
Introduction: Many clinical MRI protocols use the fluid attenuated inversion recovery (FLAIR) contrast to better delineate tissue abnormalities such as white matter lesions. Most FLAIR protocols acquire data in a 2D fashion. FLAIR images are often degraded by patient motion, especially when scanning uncooperative patients. Typical motion patterns induce inter-slice misalignment, ghosting and bl...
متن کاملShearlet-based compressed sensing for fast 3D cardiac MR imaging using iterative reweighting
High-resolution three-dimensional (3D) cardiovascular magnetic resonance (CMR) is a valuable medical imaging technique, but its widespread application in clinical practice is hampered by long acquisition times. Here we present a novel compressed sensing (CS) reconstruction approach using shearlets as a sparsifying transform allowing for fast 3D CMR (3DShearCS). Shearlets are mathematically opti...
متن کاملApplication of “Compressed Sensing” for Rapid MR Imaging
Introduction In a typical magnetic resonance imaging (MRI) experiment, samples are collected in the so-called k-space or frequency domain of the image. The number of samples needed for reconstruction at a given resolution and field of view is normally set by the Nyquist criteria and occupies a certain amount of bits in memory. However, it is commonly known that if we take the reconstructed imag...
متن کاملPotential of compressed sensing in quantitative MR imaging of cancer
Classic signal processing theory dictates that, in order to faithfully reconstruct a band-limited signal (e.g., an image), the sampling rate must be at least twice the maximum frequency contained within the signal, i.e., the Nyquist frequency. Recent developments in applied mathematics, however, have shown that it is often possible to reconstruct signals sampled below the Nyquist rate. This new...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: PLoS ONE
سال: 2013
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0056098