scholarly journals Parallel Imaging of the Cervical Spine at 3T: Optimized Trade-Off between Speed and Image Quality

2012 ◽  
Vol 33 (10) ◽  
pp. 1867-1874 ◽  
Author(s):  
J. Fruehwald-Pallamar ◽  
P. Szomolanyi ◽  
N. Fakhrai ◽  
A. Lunzer ◽  
M. Weber ◽  
...  
Keyword(s):  
Cervical Spine ◽  
Image Quality ◽  
Parallel Imaging ◽  
Trade Off

MR imaging of the cervical spine: assessment of image quality with parallel imaging compared to non-accelerated MR measurements

2006 ◽  
Vol 17 (5) ◽  
pp. 1147-1155 ◽  
Author(s):  
Iris-M. Noebauer-Huhmann ◽  
Christian Glaser ◽  
Olaf Dietrich ◽  
Claus-Peter Wallner ◽  
Wolfgang Klinger ◽  
...  
Keyword(s):  
Cervical Spine ◽  
Image Quality ◽  
Mr Imaging ◽  
Parallel Imaging

scholarly journals Feasibility of Total Variation Noise Reduction Algorithm According to Various MR-Based PET Images in a Simultaneous PET/MR System: A Phantom Study

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 319
Author(s):  
Chan-Rok Park ◽  
Seong-Hyeon Kang ◽  
Young-Jin Lee
Keyword(s):  
Image Quality ◽  
Noise Reduction ◽  
Total Variation ◽  
Parallel Imaging ◽  
Pulse Sequence ◽  
Reduction Algorithm ◽  
Median Filters ◽  
Reduction Techniques ◽  
Imaging Results ◽  
Noise Reduction Algorithm

Recently, the total variation (TV) algorithm has been used for noise reduction distribution in degraded nuclear medicine images. To acquire positron emission tomography (PET) to correct the attenuation region in the PET/magnetic resonance (MR) system, the MR Dixon pulse sequence, which is based on controlled aliasing in parallel imaging, results from higher acceleration (CAIPI; MR-ACDixon-CAIPI) and generalized autocalibrating partially parallel acquisition (GRAPPA; MR-ACDixon-GRAPPA) algorithms are used. Therefore, this study aimed to evaluate the image performance of the TV noise reduction algorithm for PET/MR images using the Jaszczak phantom by injecting 18F radioisotopes with PET/MR, which is called mMR (Siemens, Germany), compared with conventional noise-reduction techniques such as Wiener and median filters. The contrast-to-noise (CNR) and coefficient of variation (COV) were used for quantitative analysis. Based on the results, PET images with the TV algorithm were improved by approximately 7.6% for CNR and decreased by approximately 20.0% for COV compared with conventional noise-reduction techniques. In particular, the image quality for the MR-ACDixon-CAIPI PET image was better than that of the MR-ACDixon-GRAPPA PET image. In conclusion, the TV noise-reduction algorithm is efficient for improving the PET image quality in PET/MR systems.

Dose-optimized computed tomography of the cervical spine in patients with shoulder pull-down: Is image quality comparable with a standard dose protocol in an emergency setting?

2019 ◽  
Vol 120 ◽  
pp. 108655 ◽  
Author(s):  
Magdalini Tozakidou ◽  
Schu-Ren Yang ◽  
Balazs K. Kovacs ◽  
Zsolt Szucs-Farkas ◽  
Ueli Studler ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Cervical Spine ◽  
Image Quality ◽  
Standard Dose ◽  
Emergency Setting

scholarly journals Cardiac CINE MR imaging with a 32-channel cardiac coil and parallel imaging: Impact of acceleration factors on image quality and volumetric accuracy

2006 ◽  
Vol 23 (2) ◽  
pp. 222-227 ◽  
Author(s):  
Bernd J. Wintersperger ◽  
Scott B. Reeder ◽  
Konstantin Nikolaou ◽  
Olaf Dietrich ◽  
Armin Huber ◽  
...  
Keyword(s):  
Image Quality ◽  
Mr Imaging ◽  
Parallel Imaging ◽  
Cardiac Coil ◽  
Cine Mr ◽  
Cardiac Cine ◽  
Channel Cardiac Coil ◽  
Volumetric Accuracy

High-resolution renal MRA: Comparison of image quality and vessel depiction with different parallel imaging acceleration factors

2006 ◽  
Vol 24 (1) ◽  
pp. 95-100 ◽  
Author(s):  
Henrik J. Michaely ◽  
Karin A. Herrmann ◽  
Harald Kramer ◽  
Olaf Dietrich ◽  
Gerhard Laub ◽  
...  
Keyword(s):  
High Resolution ◽  
Image Quality ◽  
Parallel Imaging ◽  
Renal Mra ◽  
Parallel Imaging Acceleration

scholarly journals The effect of reconstruction and acquisition parameters for GRAPPA-based parallel imaging on the image quality

2011 ◽  
Vol 66 (2) ◽  
pp. 402-409 ◽  
Author(s):  
S. Bauer ◽  
M. Markl ◽  
M. Honal ◽  
B. A. Jung
Keyword(s):  
Image Quality ◽  
Parallel Imaging
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