scholarly journals Fast and High-Resolution Neonatal Brain MRI Through Super-Resolution Reconstruction From Acquisitions With Variable Slice Selection Direction

2021 ◽  
Vol 15 ◽  
Author(s):  
Yao Sui ◽  
Onur Afacan ◽  
Ali Gholipour ◽  
Simon K. Warfield
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Signal To Noise Ratio ◽  
Brain Mri ◽  
Super Resolution ◽  
Neonatal Brain ◽  
Signal To Noise ◽  
High Quality ◽  
Noise Ratio

The brain of neonates is small in comparison to adults. Imaging at typical resolutions such as one cubic mm incurs more partial voluming artifacts in a neonate than in an adult. The interpretation and analysis of MRI of the neonatal brain benefit from a reduction in partial volume averaging that can be achieved with high spatial resolution. Unfortunately, direct acquisition of high spatial resolution MRI is slow, which increases the potential for motion artifact, and suffers from reduced signal-to-noise ratio. The purpose of this study is thus that using super-resolution reconstruction in conjunction with fast imaging protocols to construct neonatal brain MRI images at a suitable signal-to-noise ratio and with higher spatial resolution than can be practically obtained by direct Fourier encoding. We achieved high quality brain MRI at a spatial resolution of isotropic 0.4 mm with 6 min of imaging time, using super-resolution reconstruction from three short duration scans with variable directions of slice selection. Motion compensation was achieved by aligning the three short duration scans together. We applied this technique to 20 newborns and assessed the quality of the images we reconstructed. Experiments show that our approach to super-resolution reconstruction achieved considerable improvement in spatial resolution and signal-to-noise ratio, while, in parallel, substantially reduced scan times, as compared to direct high-resolution acquisitions. The experimental results demonstrate that our approach allowed for fast and high-quality neonatal brain MRI for both scientific research and clinical studies.

Spiral CT of the pancreas

1998 ◽  
Vol 39 (1) ◽  
pp. 60-63 ◽  
Author(s):  
T. Nishiharu ◽  
Y. Yamashita ◽  
I. Ogata ◽  
S. Sumi ◽  
K. Mitsuzaki ◽  
...  
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Signal To Noise Ratio ◽  
Spiral Ct ◽  
Reconstruction Technique ◽  
Signal To Noise ◽  
Standard Size ◽  
Noise Ratio ◽  
Good Signal

Purpose: to compare the value of a retrospective targeted high-resolution spiral CT to the standard reconstruction technique in the assessment of pancreatic diseases Material and Methods: Spiral CT pancreatic images of a standard-size reconstruction protocol were compared prospectively with those of a retrospective targeted high-spatial-resolution reconstruction protocol in 30 patients. Prior to clinical evaluation, a phantom study was performed to evaluate the spatial resolution and signal-to-noise ratio of both protocols Results: the high-resolution protocol achieved a good signal-to-noise ratio with acceptable spatial resolution. Phantom studies revealed increased image noise (+17%) with an increase in spatial resolution (+100%). in patients studied with the high-resolution protocol, the increase in noise was not significant but there was a marked improvement in the definition of small details Conclusion: Images obtained with a targeted high-spatial-resolution reconstruction protocol showed superior lesion definition and vascular opacification compared with those obtained with a standard-size reconstruction protocol. This technique may have potential in the evaluation of small pancreatic abnormalities

scholarly journals Novel Configurations of Ultrahigh Frequency (≤600 MHz) Analog Frontend for High Resolution Ultrasound Measurement

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2598
Author(s):  
Min Kim ◽  
Jinhyoung Park ◽  
Qifa Zhou ◽  
Koping Shung
Keyword(s):  
High Resolution ◽  
Spatial Resolution ◽  
Signal To Noise Ratio ◽  
Ultrahigh Frequency ◽  
Ultrasound Measurement ◽  
Functional Responses ◽  
Signal To Noise ◽  
Coded Excitation ◽  
Noise Ratio ◽  
The Difference

In this article, an approach to designing and developing an ultrahigh frequency (≤600 MHz) ultrasound analog frontend with Golay coded excitation sequence for high resolution imaging applications is presented. For the purpose of visualizing specific structures or measuring functional responses of micron-sized biological samples, a higher frequency ultrasound is needed to obtain a decent spatial resolution while it lowers the signal-to-noise ratio, the difference in decibels between the signal level and the background noise level, due to the higher attenuation coefficient. In order to enhance the signal-to-noise ratio, conventional approach was to increase the transmit voltage level. However, it may cause damaging the extremely thin piezoelectric material in the ultrahigh frequency range. In this paper, we present a novel design of ultrahigh frequency (≤600 MHz) frontend system capable of performing pseudo Golay coded excitation by configuring four independently operating pulse generators in parallel and the consecutive delayed transmission from each channel. Compared with the conventional monocycle pulse approach, the signal-to-noise ratio of the proposed approach was improved by 7–9 dB without compromising the spatial resolution. The measured axial and lateral resolutions of wire targets were 16.4 µm and 10.6 µm by using 156 MHz 4 bit pseudo Golay coded excitation, respectively and 4.5 µm and 7.7 µm by using 312 MHz 4 bit pseudo Golay coded excitation, respectively.

scholarly journals Stimulation and Recording of the Hippocampus Using the Same Pt-Ir Coated Microelectrodes

2021 ◽  
Vol 15 ◽  
Author(s):  
Sahar Elyahoodayan ◽  
Wenxuan Jiang ◽  
Curtis D. Lee ◽  
Xiecheng Shao ◽  
Gregory Weiland ◽  
...  
Keyword(s):  
Evoked Potentials ◽  
Spatial Resolution ◽  
Power Efficiency ◽  
Single Unit ◽  
High Spatial Resolution ◽  
Signal To Noise Ratio ◽  
Signal To Noise ◽  
Wide Range ◽  
Noise Ratio ◽  
Improved Performance

Same-electrode stimulation and recording with high spatial resolution, signal quality, and power efficiency is highly desirable in neuroscience and neural engineering. High spatial resolution and signal-to-noise ratio is necessary for obtaining unitary activities and delivering focal stimulations. Power efficiency is critical for battery-operated implantable neural interfaces. This study demonstrates the capability of recording single units as well as evoked potentials in response to a wide range of electrochemically safe stimulation pulses through high-resolution microelectrodes coated with co-deposition of Pt-Ir. It also compares signal-to-noise ratio, single unit activity, and power efficiencies between Pt-Ir coated and uncoated microelectrodes. To enable stimulation and recording with the same microelectrodes, microelectrode arrays were treated with electrodeposited platinum-iridium coating (EPIC) and tested in the CA1 cell body layer of rat hippocampi. The electrodes’ ability to (1) inject a large range of electrochemically reversable stimulation pulses to the tissue, and (2) record evoked potentials and single unit activities were quantitively assessed over an acute time period. Compared to uncoated electrodes, EPIC electrodes recorded signals with higher signal-to-noise ratios (coated: 9.77 ± 1.95 dB; uncoated: 1.95 ± 0.40 dB) and generated lower voltages (coated: 100 mV; uncoated: 650 mV) for a given stimulus (5 μA). The improved performance corresponded to lower energy consumptions and electrochemically safe stimulation above 5 μA (>0.38 mC/cm2), which enabled elicitation of field excitatory post synaptic potentials and population spikes. Spontaneous single unit activities were also modulated by varying stimulation intensities and monitored through the same electrodes. This work represents an example of stimulation and recording single unit activities from the same microelectrode, which provides a powerful tool for monitoring and manipulating neural circuits at the single neuron level.

A mixed-effects, spatially varying coefficients model with application to multi-resolution functional magnetic resonance imaging data

2018 ◽  
Vol 28 (4) ◽  
pp. 1203-1215 ◽  
Author(s):  
Zhuqing Liu ◽  
Andreas J Bartsch ◽  
Veronica J Berrocal ◽  
Timothy D Johnson
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
High Resolution ◽  
Functional Magnetic Resonance Imaging ◽  
Spatial Resolution ◽  
Signal To Noise Ratio ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Signal To Noise ◽  
Noise Ratio

Spatial resolution plays an important role in functional magnetic resonance imaging studies as the signal-to-noise ratio increases linearly with voxel volume. In scientific studies, where functional magnetic resonance imaging is widely used, the standard spatial resolution typically used is relatively low which ensures a relatively high signal-to-noise ratio. However, for pre-surgical functional magnetic resonance imaging analysis, where spatial accuracy is paramount, high-resolution functional magnetic resonance imaging may play an important role with its greater spatial resolution. High spatial resolution comes at the cost of a smaller signal-to-noise ratio. This begs the question as to whether we can leverage the higher signal-to-noise ratio of a standard functional magnetic resonance imaging study with the greater spatial accuracy of a high-resolution functional magnetic resonance imaging study in a pre-operative patient. To answer this question, we propose to regress the statistic image from a high resolution scan onto the statistic image obtained from a standard resolution scan using a mixed-effects model with spatially varying coefficients. We evaluate our model via simulation studies and we compare its performance with a recently proposed model that operates at a single spatial resolution. We apply and compare the two models on data from a patient awaiting tumor resection. Both simulation study results and the real data analysis demonstrate that our newly proposed model indeed leverages the larger signal-to-noise ratio of the standard spatial resolution scan while maintaining the advantages of the high spatial resolution scan.

scholarly journals Deriving VIIRS High-Spatial Resolution Water Property Data over Coastal and Inland Waters Using Deep Convolutional Neural Network

2021 ◽  
Vol 13 (10) ◽  
pp. 1944
Author(s):  
Xiaoming Liu ◽  
Menghua Wang
Keyword(s):  
Neural Network ◽  
High Resolution ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Ocean Color ◽  
Super Resolution ◽  
Inland Waters ◽  
Coastal Oceans ◽  
Chl A ◽  
Color Data

The Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite has been a reliable source of ocean color data products, including five moderate (M) bands and one imagery (I) band normalized water-leaving radiance spectra nLw(λ). The spatial resolutions of the M-band and I-band nLw(λ) are 750 m and 375 m, respectively. With the technique of convolutional neural network (CNN), the M-band nLw(λ) imagery can be super-resolved from 750 m to 375 m spatial resolution by leveraging the high spatial resolution features of I1-band nLw(λ) data. However, it is also important to enhance the spatial resolution of VIIRS-derived chlorophyll-a (Chl-a) concentration and the water diffuse attenuation coefficient at the wavelength of 490 nm (Kd(490)), as well as other biological and biogeochemical products. In this study, we describe our effort to derive high-resolution Kd(490) and Chl-a data based on super-resolved nLw(λ) images at the VIIRS five M-bands. To improve the network performance over extremely turbid coastal oceans and inland waters, the networks are retrained with a training dataset including ocean color data from the Bohai Sea, Baltic Sea, and La Plata River Estuary, covering water types from clear open oceans to moderately turbid and highly turbid waters. The evaluation results show that the super-resolved Kd(490) image is much sharper than the original one, and has more detailed fine spatial structures. A similar enhancement of finer structures is also found in the super-resolved Chl-a images. Chl-a filaments are much sharper and thinner in the super-resolved image, and some of the very fine spatial features that are not shown in the original images appear in the super-resolved Chl-a imageries. The networks are also applied to four other coastal and inland water regions. The results show that super-resolution occurs mainly on pixels of Chl-a and Kd(490) features, especially on the feature edges and locations with a large spatial gradient. The biases between the original M-band images and super-resolved high-resolution images are small for both Chl-a and Kd(490) in moderately to extremely turbid coastal oceans and inland waters, indicating that the super-resolution process does not change the mean values of the original images.

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