scholarly journals Phase-aligned multiple spin-echo averaging: a simple way to improve signal-to-noise ratio of in vivo mouse spinal cord diffusion tensor image

2014 ◽  
Vol 32 (10) ◽  
pp. 1335-1343 ◽  
Author(s):  
Tsang-Wei Tu ◽  
Matthew D. Budde ◽  
Mingqiang Xie ◽  
Ying-Jr Chen ◽  
Qing Wang ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Diffusion Tensor ◽  
Signal To Noise Ratio ◽  
Spin Echo ◽  
Diffusion Tensor Image ◽  
Signal To Noise ◽  
Mouse Spinal Cord ◽  
Noise Ratio

scholarly journals Signal-to-noise ratio in the membrane potential of the owl's auditory coincidence detectors

2012 ◽  
Vol 108 (10) ◽  
pp. 2837-2845 ◽  
Author(s):  
Go Ashida ◽  
Kazuo Funabiki ◽  
Paula T. Kuokkanen ◽  
Richard Kempter ◽  
Catherine E. Carr
Keyword(s):  
Neural Circuit ◽  
Signal To Noise Ratio ◽  
Phase Locking ◽  
Low Frequency ◽  
Membrane Potentials ◽  
Signal To Noise ◽  
Theoretical Predictions ◽  
Noise Ratio ◽  
Band Limited

Owls use interaural time differences (ITDs) to locate a sound source. They compute ITD in a specialized neural circuit that consists of axonal delay lines from the cochlear nucleus magnocellularis (NM) and coincidence detectors in the nucleus laminaris (NL). Recent physiological recordings have shown that tonal stimuli induce oscillatory membrane potentials in NL neurons (Funabiki K, Ashida G, Konishi M. J Neurosci 31: 15245–15256, 2011). The amplitude of these oscillations varies with ITD and is strongly correlated to the firing rate. The oscillation, termed the sound analog potential, has the same frequency as the stimulus tone and is presumed to originate from phase-locked synaptic inputs from NM fibers. To investigate how these oscillatory membrane potentials are generated, we applied recently developed signal-to-noise ratio (SNR) analysis techniques (Kuokkanen PT, Wagner H, Ashida G, Carr CE, Kempter R. J Neurophysiol 104: 2274–2290, 2010) to the intracellular waveforms obtained in vivo. Our theoretical prediction of the band-limited SNRs agreed with experimental data for mid- to high-frequency (>2 kHz) NL neurons. For low-frequency (≤2 kHz) NL neurons, however, measured SNRs were lower than theoretical predictions. These results suggest that the number of independent NM fibers converging onto each NL neuron and/or the population-averaged degree of phase-locking of the NM fibers could be significantly smaller in the low-frequency NL region than estimated for higher best-frequency NL.

scholarly journals Sequential average segmented microscopy for high signal-to-noise ratio motion-artifact-free in vivo heart imaging

2013 ◽  
Vol 4 (10) ◽  
pp. 2095 ◽  
Author(s):  
Claudio Vinegoni ◽  
Sungon Lee ◽  
Paolo Fumene Feruglio ◽  
Pasquina Marzola ◽  
Matthias Nahrendorf ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Motion Artifact ◽  
High Signal ◽  
Signal To Noise ◽  
Heart Imaging ◽  
Noise Ratio

Optimization of signal-to-noise ratio in calculatedT1 images derived from two spin-echo images

1986 ◽  
Vol 3 (1) ◽  
pp. 63-75 ◽  
Author(s):  
F. S. Prato ◽  
D. J. Drost ◽  
T. Keys ◽  
P. Laxon ◽  
B. Comissiong ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Spin Echo ◽  
Signal To Noise ◽  
Noise Ratio

scholarly journals Self-Reset Image Sensor With a Signal-to-Noise Ratio Over 70 dB and Its Application to Brain Surface Imaging

2021 ◽  
Vol 15 ◽  
Author(s):  
Thanet Pakpuwadon ◽  
Kiyotaka Sasagawa ◽  
Mark Christian Guinto ◽  
Yasumi Ohta ◽  
Makito Haruta ◽  
...  
Keyword(s):  
Neural Activity ◽  
Signal To Noise Ratio ◽  
Image Sensor ◽  
Oxide Semiconductor ◽  
High Signal ◽  
Unstable State ◽  
Signal To Noise ◽  
Compact Size ◽  
Noise Ratio

In this study, we propose a complementary-metal-oxide-semiconductor (CMOS) image sensor with a self-resetting system demonstrating a high signal-to-noise ratio (SNR) to detect small intrinsic signals such as a hemodynamic reaction or neural activity in a mouse brain. The photodiode structure was modified from N-well/P-sub to P+/N-well/P-sub to increase the photodiode capacitance to reduce the number of self-resets required to decrease the unstable stage. Moreover, our new relay board was used for the first time. As a result, an effective SNR of over 70 dB was achieved within the same pixel size and fill factor. The unstable state was drastically reduced. Thus, we will be able to detect neural activity. With its compact size, this device has significant potential to become an intrinsic signal detector in freely moving animals. We also demonstrated in vivo imaging with image processing by removing additional noise from the self-reset operation.

Artifacts by Misalignment of Cardiac Magnetic Resonance Phased-array Coil Elements: From Simulation to In vivo Test

2019 ◽  
Vol 15 (3) ◽  
pp. 301-307
Author(s):  
Daniele De Marchi ◽  
Alessandra Flori ◽  
Nicola Martini ◽  
Giulio Giovannetti
Keyword(s):  
Cardiac Magnetic Resonance ◽  
Magnetic Resonance ◽  
Phased Array ◽  
Signal To Noise Ratio ◽  
Whole Body ◽  
Signal To Noise ◽  
Phased Array Coil ◽  
Noise Ratio ◽  
Array Coil

Background: Cardiac magnetic resonance evaluations generally require a radiofrequency coil setup comprising a transmit whole-body coil and a receive coil. In particular, radiofrequency phased-array coils are employed to pick up the signals emitted by the nuclei with high signal-tonoise ratio and a large region of sensitivity. Methods: Literature discussed different technical issues on how to minimize interactions between array elements and how to combine data from such elements to yield optimum Signal-to-Noise Ratio images. However, image quality strongly depends upon the correct coil position over the heart and of one array coil portion with respect to the other. Results: In particular, simple errors in coil positioning could cause artifacts carrying to an inaccurate interpretation of cardiac magnetic resonance images. Conclusion: This paper describes the effect of array elements misalignment, starting from coil simulation to cardiac magnetic resonance acquisitions with a 1.5 T scanner. </P><P> Phased-array coil simulation was performed using the magnetostatic approach; moreover, phantom and in vivo experiments with a commercial 8-elements cardiac phased-array receiver coil permitted to estimate signal-to-noise ratio and B1 mapping for aligned and shifted coil.

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