scholarly journals Dynamic MRI of swallowing: real-time volumetric imaging at 12 frames per second at 3 T

2021 ◽  
Author(s):  
Luuk Voskuilen ◽  
Jasper Schoormans ◽  
Oliver J. Gurney-Champion ◽  
Alfons J. M. Balm ◽  
Gustav J. Strijkers ◽  
...  
Keyword(s):  
Image Quality ◽  
Real Time ◽  
Computer Simulations ◽  
Dynamic Mri ◽  
Clinical Problem ◽  
Frame Rate ◽  
Volumetric Imaging ◽  
Golden Angle ◽  
3D Acquisition ◽  
Stack Of Stars

Abstract Objective Dysphagia or difficulty in swallowing is a potentially hazardous clinical problem that needs regular monitoring. Real-time 2D MRI of swallowing is a promising radiation-free alternative to the current clinical standard: videofluoroscopy. However, aspiration may be missed if it occurs outside this single imaged slice. We therefore aimed to image swallowing in 3D real time at 12 frames per second (fps). Materials and methods At 3 T, three 3D real-time MRI acquisition approaches were compared to the 2D acquisition: an aligned stack-of-stars (SOS), and a rotated SOS with a golden-angle increment and with a tiny golden-angle increment. The optimal 3D acquisition was determined by computer simulations and phantom scans. Subsequently, five healthy volunteers were scanned and swallowing parameters were measured. Results Although the rotated SOS approaches resulted in better image quality in simulations, in practice, the aligned SOS performed best due to the limited number of slices. The four swallowing phases could be distinguished in 3D real-time MRI, even though the spatial blurring was stronger than in 2D. The swallowing parameters were similar between 2 and 3D. Conclusion At a spatial resolution of 2-by-2-by-6 mm with seven slices, swallowing can be imaged in 3D real time at a frame rate of 12 fps.

scholarly journals Two-Dimensional Random Arrays for Real Time Volumetric Imaging

1994 ◽  
Vol 16 (3) ◽  
pp. 143-163 ◽  
Author(s):  
Richard E. Davidsen ◽  
Jørgen A. Jensen ◽  
Stephen W. Smith
Keyword(s):  
Uniform Distribution ◽  
Real Time ◽  
Imaging System ◽  
Frame Rate ◽  
Depth Of Field ◽  
System Response ◽  
Two Dimensional ◽  
Volumetric Imaging ◽  
Sparse Array ◽  
Random Array

Two-dimensional arrays are necessary for a variety of ultrasonic imaging techniques, including elevation focusing, 2-D phase aberration correction, and real time volumetric imaging. In order to reduce system cost and complexity, sparse 2-D arrays have been considered with element geometries selected ad hoc, by algorithm, or by random process. Two random sparse array geometries and a sparse array with a Mills cross receive pattern were simulated and compared to a fully sampled aperture with the same overall dimensions. The sparse arrays were designed to the constraints of the Duke University real time volumetric imaging system, which employs a wide transmit beam and receive mode parallel processing to increase image frame rate. Depth-of-field comparisons were made from simulated on-axis and off-axis beamplots at ranges from 30 to 160 mm for both coaxial and offset transmit and receive beams. A random array with Gaussian distribution of transmitters and uniform distribution of receivers was found to have better resolution and depth-of-field than both a Mills cross array and a random array with uniform distribution of both transmit and receive elements. The Gaussian random array was constructed and experimental system response measurements were made at several ranges. Comparisons of B-scan images of a tissue mimicking phantom show improvement in resolution and depth-of-field consistent with simulation results.

scholarly journals Real-time FPGA-based implementation of the AKAZE algorithm with nonlinear scale space generation using image partitioning

2021 ◽  
Author(s):  
Parastoo Soleimani ◽  
David W. Capson ◽  
Kin Fun Li
Keyword(s):  
Real Time ◽  
Memory Management ◽  
Scale Space ◽  
Image Resolution ◽  
Hardware Architecture ◽  
Frame Rate ◽  
Time Sharing ◽  
Scale Invariant ◽  
Nonlinear Scale Space ◽  
Nonlinear Scale

AbstractThe first step in a scale invariant image matching system is scale space generation. Nonlinear scale space generation algorithms such as AKAZE, reduce noise and distortion in different scales while retaining the borders and key-points of the image. An FPGA-based hardware architecture for AKAZE nonlinear scale space generation is proposed to speed up this algorithm for real-time applications. The three contributions of this work are (1) mapping the two passes of the AKAZE algorithm onto a hardware architecture that realizes parallel processing of multiple sections, (2) multi-scale line buffers which can be used for different scales, and (3) a time-sharing mechanism in the memory management unit to process multiple sections of the image in parallel. We propose a time-sharing mechanism for memory management to prevent artifacts as a result of separating the process of image partitioning. We also use approximations in the algorithm to make hardware implementation more efficient while maintaining the repeatability of the detection. A frame rate of 304 frames per second for a $$1280 \times 768$$ 1280 × 768 image resolution is achieved which is favorably faster in comparison with other work.

scholarly journals Distributed X-ray photon correlation spectroscopy data reduction using Hadoop MapReduce

2018 ◽  
Vol 25 (4) ◽  
pp. 1135-1143 ◽  
Author(s):  
Faisal Khan ◽  
Suresh Narayanan ◽  
Roger Sersted ◽  
Nicholas Schwarz ◽  
Alec Sandy
Keyword(s):  
Real Time ◽  
Photon Correlation Spectroscopy ◽  
Correlation Spectroscopy ◽  
Frame Rate ◽  
Computational Techniques ◽  
Complex Materials ◽  
Photon Correlation ◽  
X Ray ◽  
Wide Range ◽  
Recent Developments

Multi-speckle X-ray photon correlation spectroscopy (XPCS) is a powerful technique for characterizing the dynamic nature of complex materials over a range of time scales. XPCS has been successfully applied to study a wide range of systems. Recent developments in higher-frame-rate detectors, while aiding in the study of faster dynamical processes, creates large amounts of data that require parallel computational techniques to process in near real-time. Here, an implementation of the multi-tau and two-time autocorrelation algorithms using the Hadoop MapReduce framework for distributed computing is presented. The system scales well with regard to the increase in the data size, and has been serving the users of beamline 8-ID-I at the Advanced Photon Source for near real-time autocorrelations for the past five years.

scholarly journals Research on Key Technology of Real-time Video Transmission Based on Mobile Terminal

1970 ◽  
Vol 1 (2) ◽  
Author(s):  
Cao Pengfei
Keyword(s):  
Video Coding ◽  
Real Time ◽  
Video Transmission ◽  
Loss Rate ◽  
Signal To Noise Ratio ◽  
Mobile Terminal ◽  
Frame Rate ◽  
Minimum Requirement ◽  
Encapsulation Method ◽  
Real Time Transmission

In order to solve the problems existing in real-time video transmission of mobile terminals, this paper proposes the encapsulation method which is suitable for H.263 and H.264 video coding, and re- duces the extra waste of real-time transmission proto- col packets and to improve the transmission efficien- cy of the video. Experimental results show that the peak signal to noise ratio (PSNR) in H.263 and H.264 video coding mode is above 30 dB at the lowest frame rate and resolution, and the minimum requirement of video transmission has been satisfied. Rate of 24 Hz, the two encoding PSNR are more than 40 dB, videotransmission quality ideal. In addition, the two packet loss rate of about10%maximum, themaximumdelay of 400 ms or less, have reached the requirements of real-time videotransmission.

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