scholarly journals Signal-to-noise ratio and parallel imaging performance of a 16-channel receive-only brain coil array at 3.0 Tesla

2003 ◽  
Vol 51 (1) ◽  
pp. 22-26 ◽  
Author(s):  
Jacco A. de Zwart ◽  
Patrick J. Ledden ◽  
Peter van Gelderen ◽  
Jerzy Bodurka ◽  
Renxin Chu ◽  
...  
Keyword(s):  
Parallel Imaging ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
3.0 Tesla ◽  
Coil Array ◽  
Noise Ratio ◽  
Imaging Performance

scholarly journals Radar imaging with EISCAT 3D

2021 ◽  
Vol 39 (1) ◽  
pp. 119-134
Author(s):  
Johann Stamm ◽  
Juha Vierinen ◽  
Juan M. Urco ◽  
Björn Gustavsson ◽  
Jorge L. Chau
Keyword(s):  
Electron Density ◽  
Time Resolution ◽  
Signal To Noise Ratio ◽  
Radar Imaging ◽  
Signal To Noise ◽  
Range Resolution ◽  
Incoherent Scatter ◽  
E Region ◽  
Noise Ratio ◽  
Imaging Performance

Abstract. A new incoherent scatter radar called EISCAT 3D is being constructed in northern Scandinavia. It will have the capability to produce volumetric images of ionospheric plasma parameters using aperture synthesis radar imaging. This study uses the current design of EISCAT 3D to explore the theoretical radar imaging performance when imaging electron density in the E region and compares numerical techniques that could be used in practice. Of all imaging algorithms surveyed, the singular value decomposition with regularization gave the best results and was also found to be the most computationally efficient. The estimated imaging performance indicates that the radar will be capable of detecting features down to approximately 90×90 m at a height of 100 km, which corresponds to a ≈0.05∘ angular resolution. The temporal resolution is dependent on the signal-to-noise ratio and range resolution. The signal-to-noise ratio calculations indicate that high-resolution imaging of auroral precipitation is feasible. For example, with a range resolution of 1500 m, a time resolution of 10 s, and an electron density of 2×1011m-3, the correlation function estimates for radar scatter from the E region can be measured with an uncertainty of 5 %. At a time resolution of 10 s and an image resolution of 90×90 m, the relative estimation error standard deviation of the image intensity is 10 %. Dividing the transmitting array into multiple independent transmitters to obtain a multiple-input–multiple-output (MIMO) interferometer system is also studied, and this technique is found to increase imaging performance through improved visibility coverage. Although this reduces the signal-to-noise ratio, MIMO has successfully been applied to image strong radar echoes as meteors and polar mesospheric summer echoes. Use of the MIMO technique for incoherent scatter radars (ISRs) should be investigated further.

Parallel imaging compressed sensing for accelerated imaging and improved signal-to-noise ratio in MRI-based postimplant dosimetry of prostate brachytherapy

Brachytherapy ◽  
2018 ◽  
Vol 17 (5) ◽  
pp. 816-824 ◽  
Author(s):  
Jeremiah W. Sanders ◽  
Hao Song ◽  
Steven J. Frank ◽  
Tharakeswara Bathala ◽  
Aradhana M. Venkatesan ◽  
...  
Keyword(s):  
Compressed Sensing ◽  
Parallel Imaging ◽  
Signal To Noise Ratio ◽  
Prostate Brachytherapy ◽  
Signal To Noise ◽  
Postimplant Dosimetry ◽  
Accelerated Imaging ◽  
Noise Ratio

scholarly journals Comprehensive quantification of signal-to-noise ratio andg-factor for image-based andk-space-based parallel imaging reconstructions

2008 ◽  
Vol 60 (4) ◽  
pp. 895-907 ◽  
Author(s):  
Philip M. Robson ◽  
Aaron K. Grant ◽  
Ananth J. Madhuranthakam ◽  
Riccardo Lattanzi ◽  
Daniel K. Sodickson ◽  
...  
Keyword(s):  
Parallel Imaging ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Noise Ratio
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