scholarly journals Time reversal multi-target imaging technique based on eliminating the diffusion of the time reversal field

2016 ◽  
Vol 65 (20) ◽  
pp. 204102 ◽  
Author(s):  
Zang Rui ◽  
Wang Bing-Zhong ◽  
Ding Shuai ◽  
Gong Zhi-Shuang
Keyword(s):  
Time Reversal ◽  
Imaging Technique ◽  
Target Imaging ◽  
Reversal Field

A Baseline-Free Defect Imaging Technique in Plates Using Time Reversal of Lamb Waves

2011 ◽  
Vol 28 (6) ◽  
pp. 064301 ◽  
Author(s):  
Hyunjo Jeong ◽  
Sungjong Cho ◽  
Wei Wei
Keyword(s):  
Time Reversal ◽  
Lamb Waves ◽  
Imaging Technique ◽  
Defect Imaging

scholarly journals Time Reversal Reconstruction Algorithm for Photoacoustic Imaging

2021 ◽  
Author(s):  
Snigdha Dange
Keyword(s):  
Support Vector Machine ◽  
Particle Swarm Optimization ◽  
Time Reversal ◽  
Nearest Neighbor ◽  
Imaging Technique ◽  
Photoacoustic Imaging ◽  
Reconstruction Algorithm ◽  
Linear Interpolation ◽  
Support Vector ◽  
Swarm Optimization

This is the algorithm of time reversal reconstruction where a model of numerical of the problem of forward is functioned towards backwards in time of acoustics. There is an inventive imaging technique to image biomedical tissues which is also called photoacoustic imaging. In this paper, for photoacoustics imaging a time reversal reconstruction algorithm is proposed which is based on method of optimized support vector machine (SVM) interpolation, (PSO) particle swarm optimization. The images which are reconstructed from the algorithm are more exact than those of the process of interpolation of cubic convolution, interpolation of nearest neighbor and linear interpolation, whereas the numerical results are shown based on algorithm of time reversal, where it can provide quality with enough huge imaging resolution by usage of precisely less times of scan or measurements.

Producing airborne ultrasonic 3D tactile image by time reversal field rendering

2014 ◽  
Author(s):  
Seki Inoue ◽  
Yasutoshi Makino ◽  
Hiroyuki Shinoda
Keyword(s):  
Time Reversal ◽  
Tactile Image ◽  
Reversal Field

Time reversal imaging based on joint space–frequency and frequency–frequency data

2019 ◽  
Vol 11 (3) ◽  
pp. 207-214
Author(s):  
Tong Mu ◽  
Yaoliang Song
Keyword(s):  
Time Reversal ◽  
Joint Space ◽  
Data Matrix ◽  
Single Measurement ◽  
Practical Applications ◽  
Target Imaging ◽  
The Matrix ◽  
Space Frequency ◽  
Array Aperture ◽  
Value Decomposition

AbstractA new time reversal (TR) method for target imaging is proposed in this paper. Through single measurement by the antenna array, the received signals are utilized to form the space–frequency–frequency multistatic data matrix (MDM). Singular value decomposition is applied to the matrix to obtain the left singular vectors which span the signal subspace. The obtained vectors are divided into multiple subvectors by two different schemes and used to provide target signatures in the form of coarse frequency dependence and relative phase shifts that can be exploited to construct the imaging function. The performance of the proposed method is investigated through numerical simulations for both single and multiple targets, and the results are compared with the traditional TR method using the frequency–frequency MDM. It turned out that the proposed method is able to achieve high resolution with limited array aperture and shows satisfactory robustness in noise environment. Furthermore, experimental results are provided to show the availability of the method in practical applications.

scholarly journals Time Reversal Reconstruction Algorithm Based on PSO Optimized SVM Interpolation for Photoacoustic Imaging

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Mingjian Sun ◽  
Zhenghua Wu ◽  
Ting Liu ◽  
Jiajun Hu ◽  
Guanqun Wu ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Time Reversal ◽  
Nearest Neighbor ◽  
Imaging Technique ◽  
Photoacoustic Imaging ◽  
Interpolation Method ◽  
Reconstruction Algorithm ◽  
Linear Interpolation ◽  
Support Vector ◽  
Swarm Optimization

Photoacoustic imaging is an innovative imaging technique to image biomedical tissues. The time reversal reconstruction algorithm in which a numerical model of the acoustic forward problem is run backwards in time is widely used. In the paper, a time reversal reconstruction algorithm based on particle swarm optimization (PSO) optimized support vector machine (SVM) interpolation method is proposed for photoacoustics imaging. Numerical results show that the reconstructed images of the proposed algorithm are more accurate than those of the nearest neighbor interpolation, linear interpolation, and cubic convolution interpolation based time reversal algorithm, which can provide higher imaging quality by using significantly fewer measurement positions or scanning times.

The dislocation structure of a 10° [110] tilt boundary in silicon

1983 ◽  
Vol 41 ◽  
pp. 114-115
Author(s):  
B. Cunningham ◽  
D.G. Ast
Keyword(s):  
Dislocation Structure ◽  
Tilt Angle ◽  
Imaging Technique ◽  
Diamond Lattice ◽  
Tilt Boundary ◽  
Formation Mechanisms ◽  
Diffraction Contrast ◽  
Lattice Fringe ◽  
Tilt Boundaries ◽  
Chemically Vapor Deposited

There have Been a number of studies of low-angle, θ < 4°, [10] tilt boundaries in the diamond lattice. Dislocations with Burgers vectors a/2<110>, a/2<112>, a<111> and a<001> have been reported in melt-grown bicrystals of germanium, and dislocations with Burgers vectors a<001> and a/2<112> have been reported in hot-pressed bicrystals of silicon. Most of the dislocations were found to be dissociated, the dissociation widths being dependent on the tilt angle. Possible dissociation schemes and formation mechanisms for the a<001> and a<111> dislocations from the interaction of lattice dislocations have recently been given.The present study reports on the dislocation structure of a 10° [10] tilt boundary in chemically vapor deposited silicon. The dislocations in the boundary were spaced about 1-3nm apart, making them difficult to resolve by conventional diffraction contrast techniques. The dislocation structure was therefore studied by the lattice-fringe imaging technique.

X-ray microtomography

1988 ◽  
Vol 46 ◽  
pp. 998-999
Author(s):  
H.W. Deckman ◽  
B.F. Flannery ◽  
J.H. Dunsmuir ◽  
K.D' Amico
Keyword(s):  
Computed Tomography ◽  
Internal Structure ◽  
Imaging Technique ◽  
Three Dimensional ◽  
Tissue Structure ◽  
Individual Element ◽  
X Ray ◽  
Non Invasive ◽  
Panoramic Imaging ◽  
Three Dimensional Images

We have developed a new X-ray microscope which produces complete three dimensional images of samples. The microscope operates by performing X-ray tomography with unprecedented resolution. Tomography is a non-invasive imaging technique that creates maps of the internal structure of samples from measurement of the attenuation of penetrating radiation. As conventionally practiced in medical Computed Tomography (CT), radiologists produce maps of bone and tissue structure in several planar sections that reveal features with 1mm resolution and 1% contrast. Microtomography extends the capability of CT in several ways. First, the resolution which approaches one micron, is one thousand times higher than that of the medical CT. Second, our approach acquires and analyses the data in a panoramic imaging format that directly produces three-dimensional maps in a series of contiguous stacked planes. Typical maps available today consist of three hundred planar sections each containing 512x512 pixels. Finally, and perhaps of most import scientifically, microtomography using a synchrotron X-ray source, allows us to generate maps of individual element.

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