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J. Imaging, Volume 5, Issue 2 (February 2019) – 10 articles

Cover Story (view full-size image): A dusty plasma is formed by injecting micrometer-sized “dust” particles into a gaseous discharge of electrons, ions, and neutral particles. These dust particles typically acquire a high negative charge and form a massive plasma component that gives rise to many interesting novel structural and dynamical phenomena. A three-dimensional measurement of the microparticle motion is possible on the kinetic level of individual particles by stereoscopic imaging. Here, we checked different algorithms to reconstruct the three-dimensional particle trajectories. The algorithms were tested for artificial dust systems with respect to particle density, total particle number, and camera orientations. Finally, they were applied to real volumetric data measured on parabolic flights. Their performance in reconstructing particle trajectories in such dense dust clouds was analyzed. These trajectories will be used to reveal [...] Read more.
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20 pages, 10180 KiB  
Article
Evaluation of Material Appearance Under Different Spotlight Distributions Compared to Natural Illumination
by Takashi Yamazoe, Tomohiro Funaki, Yuki Kiyasu and Yoko Mizokami
J. Imaging 2019, 5(2), 31; https://doi.org/10.3390/jimaging5020031 - 21 Feb 2019
Cited by 4 | Viewed by 5860
Abstract
Solid-state lamps including Organic Light Emitting Diode (OLED) lighting could facilitate a wide variety of lighting conditions by controlling the spectral power distribution and the spatial distribution of the light source. The appearance of the surface of an object is significantly influenced by [...] Read more.
Solid-state lamps including Organic Light Emitting Diode (OLED) lighting could facilitate a wide variety of lighting conditions by controlling the spectral power distribution and the spatial distribution of the light source. The appearance of the surface of an object is significantly influenced by the lighting conditions and the constituent materials of the objects. Therefore, appearance of objects may appear to be different from expectation. Lighting condition leads to important part of accurate material recognition. We investigate whether it is possible to determine the lighting condition that results in the intended material appearance by the evaluation of this parameter under different lighting distributions compared to natural illumination. The viewing conditions of three spotlight sizes and three illuminance levels were investigated. The participants selected the viewing condition for which the appearance of fruits and vegetable food samples was the closest to the impressions learned from observing and freely holding these objects under natural reference illumination. Participants also evaluated their impressions of stimuli in each viewing condition by responding to twelve questions. The results show that the wide spotlight size condition with higher diffuseness of the illumination was selected more frequently than the narrow spotlight conditions. This suggests that the diffuseness of illumination influences the appearance of the object’s material. The results of seven-point scales suggest that their impression of stimuli was influenced by the surface properties of the objects as well as the lighting distributions. It was suggested that it is possible to set an appropriate lighting condition to facilitate material appearance similar to the expected appearance under natural illumination. Full article
(This article belongs to the Special Issue Material Appearance and Visual Understanding)
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22 pages, 1195 KiB  
Review
Algorithms for Particle Detection in Complex Plasmas
by Daniel P. Mohr, Christina A. Knapek, Peter Huber and Erich Zaehringer
J. Imaging 2019, 5(2), 30; https://doi.org/10.3390/jimaging5020030 - 21 Feb 2019
Cited by 7 | Viewed by 6914
Abstract
In complex plasmas, the behavior of freely floating micrometer sized particles is studied. The particles can be directly visualized and recorded by digital video cameras. To analyze the dynamics of single particles, reliable algorithms are required to accurately determine their positions to sub-pixel [...] Read more.
In complex plasmas, the behavior of freely floating micrometer sized particles is studied. The particles can be directly visualized and recorded by digital video cameras. To analyze the dynamics of single particles, reliable algorithms are required to accurately determine their positions to sub-pixel accuracy from the recorded images. Typically, a straightforward algorithm such as the moment method is used for this task. Here, we combine different variations of the moment method with common techniques for image pre- and post-processing (e.g., noise reduction and fitting), and we investigate the impact of the choice of threshold parameters, including an automatic threshold detection, on synthetic data with known attributes. The results quantitatively show that each algorithm and method has its own advantage, often depending on the problem at hand. This knowledge is applicable not only to complex plasmas, but useful for any kind of comparable image-based particle tracking, e.g., in the field of colloids or granular matter. Full article
(This article belongs to the Special Issue Image Processing in Soft Condensed Matter)
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11 pages, 6143 KiB  
Article
In-Situ Imaging of Molten High-Entropy Alloys Using Cold Neutrons
by Nicholas Derimow, Louis J. Santodonato, Benjamin E. MacDonald, Bryan Le, Enrique J. Lavernia and Reza Abbaschian
J. Imaging 2019, 5(2), 29; https://doi.org/10.3390/jimaging5020029 - 16 Feb 2019
Cited by 3 | Viewed by 6228
Abstract
Real-time neutron imaging was utilized to produce a movie-like series of radiographs for in-situ observation of the remixing of liquid state immiscibility that occurs in equiatomic CoCrCu with the addition of Ni. A previous neutron imaging study demonstrated that liquid state immiscibility can [...] Read more.
Real-time neutron imaging was utilized to produce a movie-like series of radiographs for in-situ observation of the remixing of liquid state immiscibility that occurs in equiatomic CoCrCu with the addition of Ni. A previous neutron imaging study demonstrated that liquid state immiscibility can be observed in-situ for the equiatomic CoCrCu alloy. In this follow-up study, equiatomic buttons of CoCrCu were placed alongside small Ni buttons inside an alumina crucible in a high-temperature vacuum furnace. The mass of the Ni buttons was specifically selected such that when melted in the same crucible as the CoCrCu buttons, the overall composition would become equiatomic CoCrCuNi. Neutron imaging was simultaneously carried out to capture 10 radiographs in 20 °C steps from 1000 °C to 1500 °C and back down to 1000 °C. This, in turn, produced a movie-like series of radiographs that allow for the observation of the buttons melting, the transition from immiscible to miscible as Ni is alloyed into the CoCrCu system, and solidification. This novel imaging process showed the phase-separated liquids remixing into a single-phase liquid when Ni dissolves into the melt, which makes this technique crucial for understanding the liquid state behavior of these complex alloy systems. As metals are not transparent to X-ray imaging techniques at this scale, neutron imaging of melting and solidification allows for the observation of liquid state phase changes in real time. Thermodynamic calculations of the isopleth for CoCrCuNix were carried out to compare the observed results to the predictions resulting from the current Thermo-Calc TCHEA3 thermodynamic database. The calculations show a very good agreement with the experimental results, as the calculations indicate that the CoCrCuNix alloy solidifies from a single-phase liquid when x ≥ 0.275, which is close to the nominal concentration of the CoCrCuNi alloy (x = 0.25). The neutron imaging shows that the solidification of CoCrCuNi results from a single-phase liquid. This is evident as no changes in the neutron attenuation were observed during the solidification of the CoCrCuNi alloy. Full article
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15 pages, 1706 KiB  
Article
Three-Dimensional Reconstruction of Individual Particles in Dense Dust Clouds: Benchmarking Camera Orientations and Reconstruction Algorithms
by Michael Himpel and André Melzer
J. Imaging 2019, 5(2), 28; https://doi.org/10.3390/jimaging5020028 - 13 Feb 2019
Cited by 7 | Viewed by 5573
Abstract
In dusty plasmas, determining the three-dimensional particle positions and trajectories of individual particles is often required. This paper benchmarks two approaches capable of reconstructing the trajectories of particles in three dimensions. The influences of the particle number, the particle number density, and the [...] Read more.
In dusty plasmas, determining the three-dimensional particle positions and trajectories of individual particles is often required. This paper benchmarks two approaches capable of reconstructing the trajectories of particles in three dimensions. The influences of the particle number, the particle number density, and the orientation of the individual cameras are studied. Additionally, the demands on the desired image quality, required for these algorithms, are discussed. The reader is given practical information for the appropriate reconstruction approach and camera positioning that should/could be used in a specific application. Full article
(This article belongs to the Special Issue Image Processing in Soft Condensed Matter)
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17 pages, 1466 KiB  
Article
Contraction Integral Equation for Three-Dimensional Electromagnetic Inverse Scattering Problems
by Yu Zhong and Kuiwen Xu
J. Imaging 2019, 5(2), 27; https://doi.org/10.3390/jimaging5020027 - 08 Feb 2019
Cited by 12 | Viewed by 5652
Abstract
Inverse scattering problems (ISPs) stand at the center of many important imaging applications, such as geophysical explorations, industrial non-destructive testing, bio-medical imaging, etc. Recently, a new type of contraction integral equation for inversion (CIE-I) has been proposed to tackle the two-dimensional electromagnetic ISPs, [...] Read more.
Inverse scattering problems (ISPs) stand at the center of many important imaging applications, such as geophysical explorations, industrial non-destructive testing, bio-medical imaging, etc. Recently, a new type of contraction integral equation for inversion (CIE-I) has been proposed to tackle the two-dimensional electromagnetic ISPs, in which the usually employed Lippmann–Schwinger integral equation (LSIE) is transformed into a new form with a modified medium contrast via a contraction mapping. With the CIE-I, the multiple scattering effects, i.e., the physical reason for the nonlinearity in the ISPs, is substantially suppressed in estimating the modified contrast, without compromising physical modeling. In this paper, we firstly propose to implement this new CIE-I for the three-dimensional ISPs. With the help of the FFT type twofold subspace-based optimization method (TSOM), when handling the highly nonlinear problems with strong scatterers, those with higher contrast and/or larger dimensions (in terms of wavelengths), the performance of the inversions with CIE-I is much better than the ones with the LSIE, wherein inversions usually converge to local minima that may be far away from the solution. In addition, when handling the moderate scatterers (those the LSIE modeling can still handle), the convergence speed of the proposed method with CIE-I is much faster than the one with the LSIE. Secondly, we propose to relax the contraction mapping condition, i.e., different contraction mappings are used in updating contrast sources and contrast, and we find that the convergence can be further accelerated. Several numerical tests illustrate the aforementioned interests. Full article
(This article belongs to the Special Issue Microwave Imaging and Electromagnetic Inverse Scattering Problems)
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16 pages, 1187 KiB  
Article
PixelBNN: Augmenting the PixelCNN with Batch Normalization and the Presentation of a Fast Architecture for Retinal Vessel Segmentation
by Henry A. Leopold, Jeff Orchard, John S. Zelek and Vasudevan Lakshminarayanan
J. Imaging 2019, 5(2), 26; https://doi.org/10.3390/jimaging5020026 - 02 Feb 2019
Cited by 47 | Viewed by 7407
Abstract
Analysis of retinal fundus images is essential for eye-care physicians in the diagnosis, care and treatment of patients. Accurate fundus and/or retinal vessel maps give rise to longitudinal studies able to utilize multimedia image registration and disease/condition status measurements, as well as applications [...] Read more.
Analysis of retinal fundus images is essential for eye-care physicians in the diagnosis, care and treatment of patients. Accurate fundus and/or retinal vessel maps give rise to longitudinal studies able to utilize multimedia image registration and disease/condition status measurements, as well as applications in surgery preparation and biometrics. The segmentation of retinal morphology has numerous applications in assessing ophthalmologic and cardiovascular disease pathologies. Computer-aided segmentation of the vasculature has proven to be a challenge, mainly due to inconsistencies such as noise and variations in hue and brightness that can greatly reduce the quality of fundus images. The goal of this work is to collate different key performance indicators (KPIs) and state-of-the-art methods applied to this task, frame computational efficiency–performance trade-offs under varying degrees of information loss using common datasets, and introduce PixelBNN, a highly efficient deep method for automating the segmentation of fundus morphologies. The model was trained, tested and cross tested on the DRIVE, STARE and CHASE_DB1 retinal vessel segmentation datasets. Performance was evaluated using G-mean, Mathews Correlation Coefficient and F1-score, with the main success measure being computation speed. The network was 8.5× faster than the current state-of-the-art at test time and performed comparatively well, considering a 5× to 19× reduction in information from resizing images during preprocessing. Full article
(This article belongs to the Special Issue Mathematical and Computational Methods in Image Processing)
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19 pages, 2340 KiB  
Article
Developments in Electrical-Property Tomography Based on the Contrast-Source Inversion Method
by Reijer Leijsen, Patrick Fuchs, Wyger Brink, Andrew Webb and Rob Remis
J. Imaging 2019, 5(2), 25; https://doi.org/10.3390/jimaging5020025 - 01 Feb 2019
Cited by 8 | Viewed by 5860
Abstract
The main objective of electrical-property tomography (EPT) is to retrieve dielectric tissue parameters from B ^ 1 + data as measured by a magnetic-resonance (MR) scanner. This is a so-called hybrid inverse problem in which data are defined inside the reconstruction domain of [...] Read more.
The main objective of electrical-property tomography (EPT) is to retrieve dielectric tissue parameters from B ^ 1 + data as measured by a magnetic-resonance (MR) scanner. This is a so-called hybrid inverse problem in which data are defined inside the reconstruction domain of interest. In this paper, we discuss recent and new developments in EPT based on the contrast-source inversion (CSI) method. After a short review of the basics of this method, two- and three-dimensional implementations of CSI–EPT are presented along with a very efficient variant of 2D CSI–EPT called first-order induced current EPT (foIC-EPT). Practical implementation issues that arise when applying the method to measured data are addressed as well, and the limitations of a two-dimensional approach are extensively discussed. Tissue-parameter reconstructions of an anatomically correct male head model illustrate the performance of two- and three-dimensional CSI–EPT. We show that 2D implementation only produces reliable reconstructions under very special circumstances, while accurate reconstructions can be obtained with 3D CSI–EPT. Full article
(This article belongs to the Special Issue Microwave Imaging and Electromagnetic Inverse Scattering Problems)
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19 pages, 2343 KiB  
Article
Comparative Study on Local Binary Patterns for Mammographic Density and Risk Scoring
by Minu George and Reyer Zwiggelaar
J. Imaging 2019, 5(2), 24; https://doi.org/10.3390/jimaging5020024 - 01 Feb 2019
Cited by 26 | Viewed by 6835
Abstract
Breast density is considered to be one of the major risk factors in developing breast cancer. High breast density can also affect the accuracy of mammographic abnormality detection due to the breast tissue characteristics and patterns. We reviewed variants of local binary pattern [...] Read more.
Breast density is considered to be one of the major risk factors in developing breast cancer. High breast density can also affect the accuracy of mammographic abnormality detection due to the breast tissue characteristics and patterns. We reviewed variants of local binary pattern descriptors to classify breast tissue which are widely used as texture descriptors for local feature extraction. In our study, we compared the classification results for the variants of local binary patterns such as classic LBP (Local Binary Pattern), ELBP (Elliptical Local Binary Pattern), Uniform ELBP, LDP (Local Directional Pattern) and M-ELBP (Mean-ELBP). A wider comparison with alternative texture analysis techniques was studied to investigate the potential of LBP variants in density classification. In addition, we investigated the effect on classification when using descriptors for the fibroglandular disk region and the whole breast region. We also studied the effect of the Region-of-Interest (ROI) size and location, the descriptor size, and the choice of classifier. The classification results were evaluated based on the MIAS database using a ten-run ten-fold cross validation approach. The experimental results showed that the Elliptical Local Binary Pattern descriptors and Local Directional Patterns extracted most relevant features for mammographic tissue classification indicating the relevance of directional filters. Similarly, the study showed that classification of features from ROIs of the fibroglandular disk region performed better than classification based on the whole breast region. Full article
(This article belongs to the Special Issue Medical Image Understanding and Analysis 2018)
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9 pages, 2338 KiB  
Article
Origami Lesion-Targeting Device for CT-Guided Interventions
by Austin J. Taylor, Sheng Xu, Bradford J. Wood and Zion Tsz Ho Tse
J. Imaging 2019, 5(2), 23; https://doi.org/10.3390/jimaging5020023 - 23 Jan 2019
Cited by 5 | Viewed by 5219
Abstract
The objective of this study is to preliminarily evaluate a lesion-targeting device for CT-guided interventions. The device is created by laser cutting the structure from a sheet of medical grade paperboard, 3D printing two radiocontrast agent grids onto the surface and folding the [...] Read more.
The objective of this study is to preliminarily evaluate a lesion-targeting device for CT-guided interventions. The device is created by laser cutting the structure from a sheet of medical grade paperboard, 3D printing two radiocontrast agent grids onto the surface and folding the structure into a rectangular prism with a viewing window. An abdominal imaging phantom was used to evaluate the device through CT imaging and the targeting of lesions for needle insertion. The lesion-targeting trials resulted in a mean targeting error of 2.53 mm (SD 0.59 mm, n = 30). The device is rigid enough to adequately support standard biopsy needles, and it attaches to the patient, reducing the risk of tissue laceration by needles held rigidly in place by an external manipulator. Additional advantages include adequate support for the insertion of multiple surgical tools at once for procedures such as composite ablation and the potential to guide off-axial needle insertion. The low-cost and disposability of the device make it well-suited for the minimally invasive image-guided therapy environment. Full article
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13 pages, 3518 KiB  
Article
Understanding Vasomotion of Lung Microcirculation by In Vivo Imaging
by Enrico Mazzuca, Andrea Aliverti and Giuseppe Miserocchi
J. Imaging 2019, 5(2), 22; https://doi.org/10.3390/jimaging5020022 - 22 Jan 2019
Cited by 9 | Viewed by 5523
Abstract
The balance of lung extravascular water depends upon the control of blood flow in the alveolar distribution vessels that feed downstream two districts placed in parallel, the corner vessels and the alveolar septal network. The occurrence of an edemagenic condition appears critical as [...] Read more.
The balance of lung extravascular water depends upon the control of blood flow in the alveolar distribution vessels that feed downstream two districts placed in parallel, the corner vessels and the alveolar septal network. The occurrence of an edemagenic condition appears critical as an increase in extravascular water endangers the thinness of the air–blood barrier, thus negatively affecting the diffusive capacity of the lung. We exposed anesthetized rabbits to an edemagenic factor (12% hypoxia) for 120 min and followed by in vivo imaging the micro-vascular morphology through a “pleural window” using a stereo microscope at a magnification of 15× (resolution of 7.2 μm). We measured the change in diameter of distribution vessels (50–200 μm) and corner vessels (<50 μm). On average, hypoxia caused a significant decrease in diameter of both smaller distribution vessels (about ~50%) and corner vessels (about ~25%) at 30 min. After 120 min, reperfusion occurred. Regional differences in perivascular interstitial volume were observed and could be correlated with differences in blood flow control. To understand such difference, we modelled imaged alveolar capillary units, obtained by Voronoi method, integrating microvascular pressure parameters with capillary filtration. Results of the analysis suggested that at 120 min, alveolar blood flow was diverted to the corner vessels in larger alveoli, which were found also to undergo a greater filtration indicating greater proneness to develop lung edema. Full article
(This article belongs to the Special Issue In-vivo Imaging)
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