scholarly journals Effect of radiofrequency shield diameter on signal‐to‐noise ratio at ultra‐high field MRI

2021 ◽  
Vol 85 (6) ◽  
pp. 3522-3530
Author(s):  
Bei Zhang ◽  
Gregor Adriany ◽  
Lance Delabarre ◽  
Jerahmie Radder ◽  
Russell Lagore ◽  
...  
Keyword(s):  
High Field ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Ultra High Field ◽  
High Field Mri ◽  
Ultra High Field Mri ◽  
Noise Ratio

scholarly journals Improving Signal to Noise Ratio in Ultra High Field Magnetic Resonance Imaging

2021 ◽  
Author(s):  
Nader Tavaf
Keyword(s):  
Human Brain ◽  
High Field ◽  
Signal To Noise Ratio ◽  
Noise Correlation ◽  
Resonance Imaging ◽  
Mr Images ◽  
Signal To Noise ◽  
Ultra High Field ◽  
Noise Ratio ◽  
Receive Array

Ultra-High Field (UHF) Magnetic Resonance Imaging (MRI) advantages, including higher image resolution, reduced acquisition time via parallel imaging, and better signal-to-noise ratio (SNR) have opened new opportunities for various clinical and research projects, including functional MRI, brain connectivity mapping, and anatomical imaging. The advancement of these UHF MRI performance metrics, especially SNR, was the primary motivation of this thesis. Unaccelerated SNR depends on receive array sensitivity profile, receiver noise correlation and static magnetic field strength. Various receive array decoupling technologies, including overlap/inductive and preamplifier decoupling, were previously utilized to mitigate noise correlation. In this dissertation, I developed a novel self-decoupling principle to isolate elements of a loop-based receive array and demonstrated, via full-wave electromagnetic/circuit co-simulations validated by bench measurements, that the self-decoupling technique provides inter-element isolation on par with overlap decoupling while self-decoupling improves SNR. I then designed and constructed the first self-decoupled 32 and 64 channel receiver arrays for human brain MR imaging at 10.5T / 447MHz. Experimental comparisons of these receive arrays with the industry’s gold-standard 7T 32 channel receiver resulted in 1.81 times and 3.53 times more average SNR using the 10.5T 32 and 64 channel receivers I built, respectively. To further improve the SNR of accelerated MR images, I developed a novel data-driven model using a customized conditional generative adversarial network (GAN) architecture for parallel MR image reconstruction and demonstrated that, when applied to human brain images subsampled with rate of 4, the GAN model results in a peak signal-to-noise ratio (PSNR) of 37.65 compared to GeneRalized Autocalibrating Partial Parallel Acquisition (GRAPPA)’s PSNR of 33.88.In summary, the works presented in this dissertation improved the SNR available for human brain imaging and provided the experimental realization of the advantages anticipated at 10.5T MRI. The insights from this thesis inform future efforts to build self-decoupled transmit arrays and high density, 128 channel loop-based receive arrays for human brain MRI especially at ultra-high field as well as future studies to utilize deep learning techniques for reconstruction and post-processing of parallel MR images.

Determination of the Best Emulsion for the Microscopy of Crystals

1981 ◽  
Vol 39 ◽  
pp. 32-33
Author(s):  
David A. Grano ◽  
Kenneth H. Downing
Keyword(s):  
Spatial Frequency ◽  
Information Transfer ◽  
Signal To Noise Ratio ◽  
Experimental Situation ◽  
Photographic Emulsion ◽  
Modulation Transfer ◽  
Signal To Noise ◽  
Frequency Space ◽  
Noise Ratio

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.

Experiments in Bright-Field Imaging with Hollow-Cone Illumination

1981 ◽  
Vol 39 ◽  
pp. 226-227
Author(s):  
W. Kunath ◽  
K. Weiss ◽  
E. Zeitler
Keyword(s):  
Signal To Noise Ratio ◽  
Carbon Support ◽  
Electronic System ◽  
Optic Axis ◽  
Hollow Cone ◽  
Signal To Noise ◽  
Bright Field ◽  
Noise Ratio ◽  
Single Field ◽  
Field Imaging

Bright-field images taken with axial illumination show spurious high contrast patterns which obscure details smaller than 15 ° Hollow-cone illumination (HCI), however, reduces this disturbing granulation by statistical superposition and thus improves the signal-to-noise ratio. In this presentation we report on experiments aimed at selecting the proper amount of tilt and defocus for improvement of the signal-to-noise ratio by means of direct observation of the electron images on a TV monitor.Hollow-cone illumination is implemented in our microscope (single field condenser objective, Cs = .5 mm) by an electronic system which rotates the tilted beam about the optic axis. At low rates of revolution (one turn per second or so) a circular motion of the usual granulation in the image of a carbon support film can be observed on the TV monitor. The size of the granular structures and the radius of their orbits depend on both the conical tilt and defocus.

Information capacity and bandwidth limitations in the SEM

1989 ◽  
Vol 47 ◽  
pp. 84-85
Author(s):  
D. C. Joy ◽  
R. D. Bunn
Keyword(s):  
Signal To Noise Ratio ◽  
Critical Dimension ◽  
Information Capacity ◽  
Acquisition Time ◽  
Signal To Noise ◽  
Sem Image ◽  
Probe Size ◽  
Minimum Number ◽  
Noise Ratio ◽  
Signal Channel

The information available from an SEM image is limited both by the inherent signal to noise ratio that characterizes the image and as a result of the transformations that it may undergo as it is passed through the amplifying circuits of the instrument. In applications such as Critical Dimension Metrology it is necessary to be able to quantify these limitations in order to be able to assess the likely precision of any measurement made with the microscope.The information capacity of an SEM signal, defined as the minimum number of bits needed to encode the output signal, depends on the signal to noise ratio of the image - which in turn depends on the probe size and source brightness and acquisition time per pixel - and on the efficiency of the specimen in producing the signal that is being observed. A detailed analysis of the secondary electron case shows that the information capacity C (bits/pixel) of the SEM signal channel could be written as :

Speech Reception in the Presence of Classroom Noise

1979 ◽  
Vol 10 (4) ◽  
pp. 221-230 ◽  
Author(s):  
Veronica Smyth
Keyword(s):  
Signal To Noise Ratio ◽  
Learning Processes ◽  
Speech Discrimination ◽  
Signal To Noise ◽  
Speech Reception ◽  
Monosyllabic Words ◽  
Noise Ratio

Three hundred children from five to 12 years of age were required to discriminate simple, familiar, monosyllabic words under two conditions: 1) quiet, and 2) in the presence of background classroom noise. Of the sample, 45.3% made errors in speech discrimination in the presence of background classroom noise. The effect was most marked in children younger than seven years six months. The results are discussed considering the signal-to-noise ratio and the possible effects of unwanted classroom noise on learning processes.

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