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At least 289 records · Page 16

Development of an assisting detection system for early infarct diagnosis

In this paper, a detection assisting system for early infarct detection is developed. This new developed method is used to assist the medical practitioners to diagnose infarct from computed tomography images of brain. Using this assisting system, the infarct could be diagnosed at earlier stages. The non-contrast computed tomography (NCCT) brain images are the data set used for this system. Detection module extracts the pixel data from NCCT brain images, and produces the colourized version of images. The proposed method showed great potential in detecting infarct, and helps medical practitioners to make earlier and better diagnoses.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Accuracy of volume measurement using 3D ultrasound and development of CT-3D US image fusion algorithm for prostate cancer radiotherapy

Purpose: To evaluate the accuracy of measuring volumes using three-dimensional ultrasound (3D US), and to verify the feasibility of the replacement of CT-MR fusion images with CT-3D US in radiotherapy treatment planning. Methods: Phantoms, consisting of water, contrast agent, and agarose, were manufactured. The volume was measured using 3D US, CT, and MR devices. A CT-3D US and MR-3D US image fusion software was developed using the Insight Toolkit library in order to acquire three-dimensional fusion images. The quality of the image fusion was evaluated using metric value and fusion images. Results: Volume measurement, using 3D US, shows a 2.8 {+-} 1.5% error, 4.4 {+-} 3.0% error for CT, and 3.1 {+-} 2.0% error for MR. The results imply that volume measurement using the 3D US devices has a similar accuracy level to that of CT and MR. Three-dimensional image fusion of CT-3D US and MR-3D US was successfully performed using phantom images. Moreover, MR-3D US image fusion was performed using human bladder images. Conclusions: 3D US could be used in the volume measurement of human bladders and prostates. CT-3D US image fusion could be used in monitoring the target position in each fraction of external beam radiation therapy. Moreover, the feasibility of replacing the CT-MR image fusion to the CT-3D US in radiotherapy treatment planning was verified.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Quantitative analysis of autoradiographic image intensification using Thiourea-S35

Photographic images enhanced by the method of Thiourea-S35 autoradiography are evaluated in terms of signal-to-noise ratio, detective quantum efficiency (DQE), and Wiener spectrum analysis using digitized images. It is determined that the original signal-to-noise ratio is not degraded by the intensification process which allows an increase in the practical working DQE as a function of density. These results apply at all spatial frequencies that were tested. The advantage given by autoradiography is the ability to produce usable images from emulsions originally exposed to the low densities corresponding to maximum DQE and movement of faint image densities above the level of the threshold for detection.

Askins, B. S.↗

Entanglement Enabled Intensity Interferometry of different wavelengths of light

Highlights: • We use quantum entanglement to erase the color of photons for a new imaging method. • Can achieve higher resolution imaging by accessing hidden phase information. • We detail practical experimental designs to implement our theoretical protocols. We propose methods to perform intensity interferometry of photons having two different wavelengths. Distinguishable particles typically cannot interfere with each other, but we overcome that obstacle by processing the particles via entanglement and projection so that they lead to the same final state at the detection apparatus. Specifically, we discuss how quasi-phase-matched nonlinear crystals can be used to convert a quantum superposition of light of different wavelengths onto a common wavelength, while preserving the phase information essential for their meaningful interference. We thereby gain access to a host of new observables, which can probe subtle frequency correlations and entanglement. Further, we generalize the van Cittert–Zernike formula for the intensity interferometry of extended sources, demonstrate how our proposal supports enhanced resolution of sources with different spectral character, and suggest potential applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An improved back projection algorithm of ultrasound tomography

Binary logic back projection algorithm is improved in this work for the development of fast ultrasound tomography system with a better effect of image reconstruction. The new algorithm is characterized by an extra logical value ‘2’ and dual-threshold processing of collected raw data. To compare with the original algorithm, a numerical simulation was conducted by the verification of COMSOL simulations formerly, and then a set of ultrasonic tomography system is established to perform the experiments of one, two and three cylindrical objects. The object images are reconstructed through the inversion of signals matrix acquired by the transducer array after a preconditioning, while the corresponding spatial imaging errors can obviously indicate that the improved back projection method can achieve modified inversion effect.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantum-Compatible Variational Segmentation for Image-to-Image Wildfire Detection Using Satellite Data

Wildfire occurrences have been increasing for the past decade, leaving devastating traces across the world. In the recent efforts, remote sensing and airborne missions have been utilized to better understand and manage wildfires. This has resulted in an exponential increase in volume of remote sensing data, which has pushed the need for intelligent automation of data extraction for wildfire studies. Machine learning offers accurate automation in detecting such natural anomalies and enable decision-makers to take actions in a timely manner. Recent advances in machine learning algorithms, namely probabilistic generative methods, allow researchers and decisionmakers to step beyond detection and study “what-if” scenarios for wildfire occurrences. Additionally, they offer better imitations to the stochastic behavior of nature, and wildfire events. However, optimizing the performance of these probabilistic generative models is a computationally expensive process, specially using digital computers. On the other hand, quantum computers have recently shown a promise to reduce computationally costly training of such models and provide performance improvements. There is a body of research investigating the potential for improved machine learning methods in which key operations are performed on a quantum computer. In this study, we propose a probabilistic image-toimage segmentation approach combining a very well-known segmentation method, U-NET, with a Conditional Variational Auto-Encoder (CVAE) to not only detect wildfires but also describe the stochasticity of the phenomenon and be capable of running “what-if” scenarios. Our proposed model is compatible with training on quantum computers, which results in a quantum-assisted image-to-image segmentation approach and can be used to benchmark the potential benefit of quantum computing over the classical one.

quantum↗

Evaluation of negative ion distribution changes by image processing diagnostic

Distributions of hydrogen Balmer-α (H{sub α}) intensity and its reduction behavior close to a plasma grid (PG) surface have been observed by a spectrally selective imaging system in an arc discharge type negative hydrogen ion source in National Institute for Fusion Science. H{sub α} reduction indicates a reduction of negative hydrogen ions because the mutual neutralization process between H{sup +} and H{sup −} ions causes the dominant excitation process for H{sub α} emission in the rich H{sup −} condition such as in ionic plasma. We observed a significant change in H{sub α} reduction distribution due to change in the bias voltage, which is used to suppress the electron influx. Small H{sub α} reduction in higher bias is likely because the production of negative ions is suppressed by the potential difference between the plasma and PG surface.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Optimization of phosphor-based detector design for oblique x-ray incidence in digital breast tomosynthesis

Purpose: In digital breast tomosynthesis (DBT), a volumetric reconstruction of the breast is generated from a limited range of x-ray projections. One trade-off of DBT is resolution loss in the projections due to non-normal (i.e., oblique) x-ray incidence. Although degradation in image quality due to oblique incidence has been studied using empirical data and Monte Carlo simulations, a theoretical treatment has been lacking. The purpose of this work is to extend Swank's calculations of the transfer functions of turbid granular phosphors to oblique incidence. The model is ultimately used as a tool for optimizing the design of DBT detectors. Methods: A quantum-limited system and 20 keV x-rays are considered. Under these assumptions, the modulation transfer function (MTF) and noise power spectra (NPS) are derived using the diffusion approximation to the Boltzmann equation to model optical scatter within the phosphor. This approach is applicable to a nonstructured scintillator such as gadolinium oxysulfide doped with terbium (Gd{sub 2}O{sub 2}S:Tb), which is commonly used in breast imaging and which can reasonably approximate other detector materials. The detective quantum efficiency (DQE) is then determined from the Nishikawa formulation, where it is written as the product of the x-ray quantum detection efficiency, the Swank factor, and the Lubberts fraction. Transfer functions are calculated for both front- and back-screen configurations, which differ by positioning the photocathode at the exit or entrance point of the x-ray beam, respectively. Results: In the front-screen configuration, MTF and DQE are found to have considerable angular dependence, while NPS is shown to vary minimally with projection angle. As expected, the high frequency MTF and DQE are degraded substantially at large angles. By contrast, all transfer functions for the back-screen configuration have the advantage of significantly less angular dependence. Using these models, we investigated the possibility for optimizing the design of DBT detectors. As an example optimization strategy, the phosphor thickness which maximizes the DQE at a fixed frequency is analyzed. This work demonstrates that the optimal phosphor thickness for the front-screen is angularly dependent, shifting to lower thickness at higher angles. Conversely, the back-screen is not optimized by a single thickness but instead attains reasonably high DQE values over a large range of thicknesses. Although the back-screen configuration is not suited for current detectors using a glass substrate, it may prove to be preferred in future detectors using newly proposed plastic thin-film transistor (TFT) substrates. Conclusions: Using the diffusion approximation to the Boltzmann equation to model the spread of light in a scintillator, this paper develops an analytical model of MTF, NPS, and DQE for a phosphor irradiated obliquely. The model is set apart from other studies on oblique incidence in being derived from first principles. This work has applications in the optimization of DBT detector design.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Matrix phased array (MPA) imaging technology for resistance spot welds

A three-dimensional MPA probe has been incorporated with a high speed phased array electronic board to visualize nugget images of resistance spot welds. The primary application area of this battery operated portable MPA ultrasonic imaging system is in the automotive industry which a conventional destructive testing process is commonly adopted to check the quality of resistance spot welds in auto bodies. Considering an average of five-thousand spot welds in a medium size passenger vehicle, the amount of time and effort given to popping the welds and measuring nugget size are immeasurable in addition to the millions of dollars' worth of scrap metals recycled per plant per year. This wasteful labor intensive destructive testing process has become less reliable as auto body sheet metal has transitioned from thick and heavy mild steels to thin and light high strength steels. Consequently, the necessity of developing a non-destructive inspection methodology has become inevitable. In this paper, the fundamental aspects of the current 3-D probe design, data acquisition algorithms, and weld nugget imaging process are discussed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Low temperature multi-alkali photocathode processing technique for sealed intensified CCD tubes

A low temperature photocathode process has been used to fabricate an intensified CCD visual photocathode image tube, by incorporating a thinned, backside-illumined CCD as the target anode of a digicon tube of Hubble Space Telescope (HST) design. The CCD digicon tube employs the HST's sodium bialkali photocathode and MgF2 substrate, thereby allowing a direct photocathode quantum efficiency comparison between photocathodes produced by the presently employed low temperature process and those of the conventional high temperature process. Attention is given to the processing chamber used, as well as the details of gas desorption and photocathode processing.

Doliber, D. L.↗

Frequency-domain computing using nonlinear acoustic-wave device on lithium niobate

Abstract Multiply-accumulation are crucial computing operations in signal processing, numerical simulations, and machine learning. In recent years, optical analog approaches have demonstrated higher computing performance and better power efficiency than their digital counterparts. However, analog computing chips usually need large areas and complex structures for parallel computing, as a single device element only executes one computing operation at a single time. Here, we demonstrate frequency-domain computing using the nonlinear acoustic-wave devices on lithium niobate, featuring a normalized external second-harmonic generation conversion efficiency of ~ 5.7 × 10-4 W-1. The second-order sum-frequency nonlinear process of lithium niobate enables multiplication of inputs encoded in the frequency domain. Compared to the analog schemes, our device features a notably simpler design, and nanofabrication requires only one lift-off. Using a single acoustic-wave device within an area of 0.03 mm2, we can simultaneously conduct over 130,000 multiply-accumulation operations. Our acoustic-wave device shows applications in real and complex vector convolutions and image processing. This demonstration sets the stage for experimental realizations into frequency-domain integrated nonlinear acoustic computing systems, potentially shaping future developments in acoustic neural networks and quantum computing.

chai, mingzhao (ORCID:0009000466226341)↗

Temporal and spectral imaging with micro-CT

Purpose: Micro-CT is widely used for small animal imaging in preclinical studies of cardiopulmonary disease, but further development is needed to improve spatial resolution, temporal resolution, and material contrast. We present a technique for visualizing the changing distribution of iodine in the cardiac cycle with dual source micro-CT. Methods: The approach entails a retrospectively gated dual energy scan with optimized filters and voltages, and a series of computational operations to reconstruct the data. Projection interpolation and five-dimensional bilateral filtration (three spatial dimensions + time + energy) are used to reduce noise and artifacts associated with retrospective gating. We reconstruct separate volumes corresponding to different cardiac phases and apply a linear transformation to decompose these volumes into components representing concentrations of water and iodine. Since the resulting material images are still compromised by noise, we improve their quality in an iterative process that minimizes the discrepancy between the original acquired projections and the projections predicted by the reconstructed volumes. The values in the voxels of each of the reconstructed volumes represent the coefficients of linear combinations of basis functions over time and energy. We have implemented the reconstruction algorithm on a graphics processing unit (GPU) with CUDA. We tested the utility of the technique in simulations and applied the technique in an in vivo scan of a C57BL/6 mouse injected with blood pool contrast agent at a dose of 0.01 ml/g body weight. Postreconstruction, at each cardiac phase in the iodine images, we segmented the left ventricle and computed its volume. Using the maximum and minimum volumes in the left ventricle, we calculated the stroke volume, the ejection fraction, and the cardiac output. Results: Our proposed method produces five-dimensional volumetric images that distinguish different materials at different points in time, and can be used to segment regions containing iodinated blood and compute measures of cardiac function. Conclusions: We believe this combined spectral and temporal imaging technique will be useful for future studies of cardiopulmonary disease in small animals.

60 APPLIED LIFE SCIENCES↗

Detecting brain tumor in computed tomography images using Markov random fields and fuzzy C-means clustering techniques

Brain tumors, are an abnormal growth of tissues in the brain. They may arise in people of any age. They must be detected early, diagnosed accurately, monitored carefully, and treated effectively in order to optimize patient outcomes regarding both survival and quality of life. Manual segmentation of brain tumors from CT scan images is a challenging and time consuming task. Size and location accurate detection of brain tumor plays a vital role in the successful diagnosis and treatment of tumors. Brain tumor detection is considered a challenging mission in medical image processing. The aim of this paper is to introduce a scheme for tumor detection in CT scan images using two different techniques Hidden Markov Random Fields (HMRF) and Fuzzy C-means (FCM). The proposed method has been developed in this research in order to construct hybrid method between (HMRF) and threshold. These methods have been applied on 4 different patient data sets. The result of comparison among these methods shows that the proposed method gives good results for brain tissue detection, and is more robust and effective compared with (FCM) techniques.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Atomic resolution scanning transmission electron microscopy at liquid helium temperatures for quantum materials

Fundamental quantum phenomena in condensed matter, ranging from correlated electron systems to quantum information processors, manifest their emergent characteristics and behaviors predominantly at low temperatures. This necessitates the use of liquid helium (LHe) cooling for experimental observation. Atomic resolution scanning transmission electron microscopy combined with LHe cooling (cryo-STEM) provides a powerful characterization technique to probe local atomic structural modulations and their coupling with charge, spin and orbital degrees-of-freedom in quantum materials. However, achieving atomic resolution in cryo-STEM is exceptionally challenging, primarily due to sample drifts arising from temperature changes and noises associated with LHe bubbling, turbulent gas flow, etc. In this work, we demonstrate atomic resolution cryo-STEM imaging at LHe temperatures using a commercial side-entry LHe cooling holder. Firstly, we examine STEM imaging performance as a function of He gas flow rate, identifying two primary noise sources: He-gas pulsing and He-gas bubbling. Secondly, we propose two strategies to achieve low noise conditions for atomic resolution STEM imaging: either by temporarily suppressing He gas flow rate using the needle valve or by acquiring images during the natural warming process. Lastly, we show the applications of image acquisition methods and image processing techniques in investigating structural phase transitions in Cr 2 Ge 2 Te 6 , CuIr 2 S 4 , and CrCl 3 . In conclusion, our findings represent an advance in the field of atomic resolution electron microscopy imaging for quantum materials and devices at LHe temperatures, which can be applied to other commercial side-entry LHe cooling TEM holders.

36 MATERIALS SCIENCE↗

A Novel Gradient Projection Approach for Fourier-Based Image Restoration

This work deals with the ill-posed inverse problem of reconstructing a two-dimensional image of an unknown object starting from sparse and nonuniform measurements of its Fourier Transform. In particular, if we consider a priori information about the target image (e.g., the nonnegativity of the pixels), this inverse problem can be reformulated as a constrained optimization problem, in which the stationary points of the objective function can be viewed as the solutions of a deconvolution problem with a suitable kernel. We propose a fast and effective gradient-projection iterative algorithm to provide regularized solutions of such a deconvolution problem by early stopping the iterations. Preliminary results on a real-world application in astronomy are presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Four-wave-mixing gap solitons

We report an experimental demonstration of generating gap soliton trains in a four-wave-mixing (FWM) signal. Such spatial FWM surfacelike gap soliton trains are induced in a periodically modulated self-defocusing atomic medium by the cross-phase modulation, which can be reshaped under different experimental conditions, such as different atomic densities, nonlinear dispersions, and dressing fields. Controlling spatial gap solitons can have important applications in image memory, processing, and communication.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An iterative method for tomographic x-ray perfusion estimation in a decomposition model-based approach

Purpose: X-ray based tomographic blood perfusion imaging requires recovery of contrast time-attenuation-curves from dynamic projection data. When using slowly rotating imaging systems, this task is challenging due to nonsimultaneous projection acquisition. A dynamic reconstruction method is proposed that aims at compensating the lack of simultaneously acquired information by incorporating prior knowledge about the expected temporal contrast dynamics. Methods: A decomposition model using temporal basis functions to approximate time-attenuation-curves is integrated into an iterative tomographic reconstruction method. The computationally efficient implementation of the proposed approach makes use of standard forward-projections and backprojections, as well as scalar products in image space. The critical issue of projection noise propagation is tackled by the application of regularization which is realized by the early stopping of iteration cycles and by the proper selection of smooth temporal basis functions. The performance of the proposed dynamic reconstruction approach is evaluated in a simulation study concerning various aspects: Noise propagation and regularization, specification of the temporal model, and type of acquisition mode. Results: The evaluation based on dynamic phantom data indicates that tomographic recovery of contrast time-attenuation-curves in tissue can be achieved with an average range of accuracy of {approx}2% (with respect to dynamic peak attenuation) under ideal noise-free conditions. The relative estimation error for arterial time-attenuation-curves is in the range of 8%, which is due to faster contrast dynamics in the artery. In general, performance depends on the level of acquired information contained in the projection data, which is mainly influenced by the type of rotational acquisition mode; restrictions in angular range and speed can lead to limited accuracy. The analysis of propagated projection noise in a statistical bias-variance framework reveals relative noise levels in estimated time-attenuation-curves of 3%-4% in tissue regions and below 1% in vessels when using optimized settings for regularization. Here, the effect of noise suppression depends on the interrelation between the number of iteration cycles and the constraints imposed by the temporal decomposition model. Conclusions: For usage with slowly rotating imaging systems, the presented model-based iterative dynamic reconstruction method is capable of recovering contrast time-attenuation-curves related to tissue perfusion. The proposed regularization framework is an effective means to limit the impact of projection noise, which is a factor dominating estimation accuracy in tissue regions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Resolution enhancement of lung 4D-CT data using multiscale interphase iterative nonlocal means

Purpose: Four-dimensional computer tomography (4D-CT) has been widely used in lung cancer radiotherapy due to its capability in providing important tumor motion information. However, the prolonged scanning duration required by 4D-CT causes considerable increase in radiation dose. To minimize the radiation-related health risk, radiation dose is often reduced at the expense of interslice spatial resolution. However, inadequate resolution in 4D-CT causes artifacts and increases uncertainty in tumor localization, which eventually results in extra damages of healthy tissues during radiotherapy. In this paper, the authors propose a novel postprocessing algorithm to enhance the resolution of lung 4D-CT data. Methods: The authors' premise is that anatomical information missing in one phase can be recovered from the complementary information embedded in other phases. The authors employ a patch-based mechanism to propagate information across phases for the reconstruction of intermediate slices in the longitudinal direction, where resolution is normally the lowest. Specifically, the structurally matching and spatially nearby patches are combined for reconstruction of each patch. For greater sensitivity to anatomical details, the authors employ a quad-tree technique to adaptively partition the image for more fine-grained refinement. The authors further devise an iterative strategy for significant enhancement of anatomical details. Results: The authors evaluated their algorithm using a publicly available lung data that consist of 10 4D-CT cases. The authors' algorithm gives very promising results with significantly enhanced image structures and much less artifacts. Quantitative analysis shows that the authors' algorithm increases peak signal-to-noise ratio by 3-4 dB and the structural similarity index by 3%-5% when compared with the standard interpolation-based algorithms. Conclusions: The authors have developed a new algorithm to improve the resolution of 4D-CT. It outperforms the conventional interpolation-based approaches by producing images with the markedly improved structural clarity and greatly reduced artifacts.

60 APPLIED LIFE SCIENCES↗