Evaluation of single scattering correction method in compton imaging system

2021 ◽  
pp. 165568
Author(s):  
Donghwan Kim ◽  
Mizuki Uenomachi ◽  
Kenji Shimazoe ◽  
Hiroyuki Takahashi
Keyword(s):  
Imaging System ◽  
Correction Method ◽  
Single Scattering ◽  
Compton Imaging ◽  
Scattering Correction

Homography Transformation Correction Method for Position Error Generated in Readout Circuit Based on Resistive Network for the Compton Imaging System

2020 ◽  
Vol 206 (7) ◽  
pp. 1075-1085
Author(s):  
Su-Jin Jeon ◽  
Jae-Sang Lee ◽  
Do-Hyun Kim ◽  
Seok-Ho Hong ◽  
Chun-Sik Lee ◽  
...  
Keyword(s):  
Imaging System ◽  
Correction Method ◽  
Position Error ◽  
Readout Circuit ◽  
Resistive Network ◽  
Compton Imaging ◽  
Homography Transformation

Research on Flat Field Correction Method in Adaptive Optics Retinal Imaging System

2011 ◽  
Vol 31 (12) ◽  
pp. 1211001 ◽  
Author(s):  
孔宁宁 Kong Ningning ◽  
李抄 Li Chao ◽  
夏明亮 Xia Mingliang ◽  
齐岳 Qi Yue ◽  
李大禹 Li Dayu ◽  
...  
Keyword(s):  
Adaptive Optics ◽  
Imaging System ◽  
Retinal Imaging ◽  
Correction Method ◽  
Flat Field

scholarly journals Radiation correction method for infrared polarization imaging system with front-mounted polarizer

2016 ◽  
Vol 24 (23) ◽  
pp. 26414 ◽  
Author(s):  
Shuo Li ◽  
Weiqi Jin ◽  
Runqiu Xia ◽  
Li Li ◽  
Xia Wang
Keyword(s):  
Imaging System ◽  
Correction Method ◽  
Polarization Imaging ◽  
Radiation Correction

scholarly journals A Deep Learning-Based Scatter Correction of Simulated X-ray Images

Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 944 ◽  
Author(s):  
Heesin Lee ◽  
Joonwhoan Lee
Keyword(s):  
Deep Learning ◽  
Image Quality ◽  
Imaging System ◽  
Scatter Correction ◽  
Similarity Index ◽  
Real Data ◽  
Correction Method ◽  
Training Data ◽  
X Ray ◽  
Scatter Reduction

X-ray scattering significantly limits image quality. Conventional strategies for scatter reduction based on physical equipment or measurements inevitably increase the dose to improve the image quality. In addition, scatter reduction based on a computational algorithm could take a large amount of time. We propose a deep learning-based scatter correction method, which adopts a convolutional neural network (CNN) for restoration of degraded images. Because it is hard to obtain real data from an X-ray imaging system for training the network, Monte Carlo (MC) simulation was performed to generate the training data. For simulating X-ray images of a human chest, a cone beam CT (CBCT) was designed and modeled as an example. Then, pairs of simulated images, which correspond to scattered and scatter-free images, respectively, were obtained from the model with different doses. The scatter components, calculated by taking the differences of the pairs, were used as targets to train the weight parameters of the CNN. Compared with the MC-based iterative method, the proposed one shows better results in projected images, with as much as 58.5% reduction in root-mean-square error (RMSE), and 18.1% and 3.4% increases in peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM), on average, respectively.

Development of electron-tracking Compton imaging system with 30-μm SOI pixel sensor

2017 ◽  
Vol 12 (01) ◽  
pp. C01045-C01045 ◽  
Author(s):  
Y. Yoshihara ◽  
K. Shimazoe ◽  
Y. Mizumachi ◽  
H. Takahashi ◽  
K. Kamada ◽  
...  
Keyword(s):  
Imaging System ◽  
Compton Imaging

Computer Simulations of Speckle in B-Scan Images

1983 ◽  
Vol 5 (4) ◽  
pp. 308-330 ◽  
Author(s):  
D.R. Foster ◽  
M. Arditi ◽  
F.S. Foster ◽  
M.S. Patterson ◽  
J.W. Hunt
Keyword(s):  
Imaging System ◽  
Three Dimensional ◽  
Single Scattering ◽  
Acoustic Properties ◽  
Ultrasound Images ◽  
Second Order Statistics ◽  
Diagnostic Potential ◽  
Scattering Volume ◽  
B Scan Images ◽  
Pulse Echo

The granularity or speckle in medical ultrasound images tends to mask the presence of small lesions. As well, artifactual filling in of anechoic regions such as cysts, reduces the diagnostic potential of the images. These effects depend not only on the acoustic properties of the tissue but also are strongly influenced by the imaging system, especially the transducer geometry. To study the effect of the transducer on the final B-scan image, a computer model has been developed simulating the interaction of ultrasound with a simple scattering medium. This model, incorporating the position dependence of the point response of the transducer, is based on single scattering from a collection of points positioned randomly in a three-dimensional volume. Using this approach, B-scan images showing speckle have been generated for different transducer geometries. Inclusion of a 2.6 mm void mimicking a cyst within the three-dimensional scattering volume has allowed us to predict the cyst contrast in the image for the different transducer systems. Experimental B-scan images of a scattering phantom were obtained using the different pulse echo systems. Quantitative assessment using first and second order statistics of the images shows good agreement between experiment and theory.

An intensity correction method combined with plasma position information for laser-induced breakdown spectroscopy

2017 ◽  
Vol 32 (12) ◽  
pp. 2371-2377 ◽  
Author(s):  
P. Zhang ◽  
L. X. Sun ◽  
H. B. Yu ◽  
P. Zeng ◽  
L. F. Qi ◽  
...  
Keyword(s):  
Spectral Data ◽  
Imaging System ◽  
Positional Information ◽  
Correction Method ◽  
Laser Induced Breakdown Spectroscopy ◽  
Position Information ◽  
Breakdown Spectroscopy ◽  
Plasma Position ◽  
Spectral Signal ◽  
Laser Induced Breakdown

The uncertainty of the spectral data is one of the most important issues for LIBS. To reduce the uncertainty, an imaging system was deployed and a model was built based on both the spectral signal and the positional information in this work.

scholarly journals Display In the Wild (DIW): An Adaptive Projection-Imaging System to Screen Geometry in Real Time

2018 ◽  
Author(s):  
Byungyong Ryu ◽  
Sung-Ho Bae
Keyword(s):  
Real Time ◽  
Imaging System ◽  
Flat Space ◽  
Calibration Method ◽  
Correction Method ◽  
Distortion Correction ◽  
Surface Boundary ◽  
Planar Surfaces ◽  
Display Position ◽  
In The Wild

TVs and monitors are among the most widely used displays in various environments. However, they have limitations in their physical display conditions, such as a fixed size/position and a rigid/flat space. In this paper, we suggest a new "Display In the Wild" (DIW) concept to overcome the aforementioned problems. Our proposed DIW system allows us to display a flexibly large screen on dynamic non-planar surfaces at an arbitrary display position. To implement our DIW concept practically, we choose a projector as the hardware configuration in order to a generate screen anywhere with different sizes. However, distortion occurs when the projector displays content on a surface that is dynamic and/or non-planar. Therefore, we propose a distortion correction method for DIW to overcome the aforementioned surface-constraints. Since projectors are not capture devices, we propose using a depth camera to determine the distortions on the surfaces quickly. We also propose DIW-specific calibration and fast/precise correction methods. Our calibration method is constructed to easily and quickly detect the projection surface, and also allows our proposed system to accommodate the intrinsic parameters such as a display resolution and field of view. We accomplish a fast undistortion process of the projector by considering only surface boundary pixels, which enables our method to run in real time. In our comprehensive experiments, the proposed DIW system generates undistorted screens such as TVs and monitors on dynamic non-planar surfaces at an arbitrary display position with Unmanned Aerial Vehicles (UAVs) in a fast and accurate manner, demonstrating its usefullness in practical DIW scenarios.

scholarly journals Aethalometer multiple scattering correction C<sub>ref</sub> for mineral dust aerosols

2017 ◽  
Author(s):  
Claudia Di Biagio ◽  
Paola Formenti ◽  
Mathieu Cazaunau ◽  
Edouard Pangui ◽  
Nicholas Marchand ◽  
...  
Keyword(s):  
Absorption Coefficient ◽  
Multiple Scattering ◽  
Mineral Dust ◽  
Single Scattering ◽  
Ambient Aerosols ◽  
Dust Aerosols ◽  
Scattering Coefficients ◽  
Scattering Correction ◽  
The Difference ◽  
Mineral Dust Aerosols

Abstract. In this study we provide a first estimate of the aethalometer multiple scattering correction Cref for mineral dust aerosols. The Cref at 450 and 660 nm was obtained from the direct comparison of aethalometer data (Magee Sci. AE31) with the absorption coefficient calculated as the difference between the extinction and scattering coefficients measured by a CAPS PMex and a nephelometer at 450 nm and the absorption coefficient from a MAAP (Multi-Angle Absorption Photometer) at 660 nm. Measurements were performed on seven dust aerosol samples generated in the laboratory by the mechanical shaking of natural parent soils issued from different source regions worldwide. The single scattering albedo (SSA) at 450 and 660 nm and the size distribution of the aerosols were also measured. Cref for mineral dust varies between 1.81 and 2.56 for a SSA of 0.85–0.96 at 450 nm and between 1.75 and 2.28 for a SSA of 0.98–0.99 at 660 nm. The calculated mean Cref for dust is 2.09 (± 0.22) at 450 nm and 1.92 (± 0.17) at 660 nm. With this new Cref the dust absorption coefficient by aethalometer is about 2 % (450 nm) and 11 % (660 nm) higher than that obtained by using Cref = 2.14, usually assumed in the literature. This difference induces up to 3 % change in the dust SSA. The Cref seems independent of the particle fine and coarse size fractions, and so the obtained Cref can be applied to dust both close to sources and following transport. Additional experiments performed with pure kaolinite mineral and polluted ambient aerosols indicate a Cref of 2.49 (± 0.02) and 2.32 (± 0.01) at 450 and 660 nm (SSA = 0.96–0.97) for kaolinite, and a Cref of 2.32 (± 0.36) at 450 nm and 2.32 (± 0.35) at 660 nm for pollution aerosols (SSA = 0.62–0.87 at 450 nm and 0.42–0.76 at 660 nm).

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