Iterative X-ray computed tomography (CT) algorithms have the potential for producing high-quality images but are computationally very demanding, especially when applied to high-resolution problems. Focusing on simultaneous iterative reconstruction technique (SIRT), we provide an eigenvalue based scheme automatically determining a near-optimal value of relaxation parameter. This accelerates convergence rate SIRT point where only half number iterations normally required is needed. We also...

High spatial resolution (∼13.7 mm/pixel) neutron tomography was performed on partially water-saturated compacted silica sand specimens with two different grain morphologies (round and angular) at Helmholtz Zentrum Berlin using cold neutrons the radiography beam line. A specimen mixed heavy water imaged for contrast comparison purposes. Microfocus X-ray imaging also these slightly higher (∼11.2 geometric magnification to locate solid phase (silica particle boundaries) more precisely. Image...

Purpose: Neural network image reconstruction directly from measurement data is a relatively new field of research, which until now has been limited to producing small single-slice images (e.g., 1 × 128 128). We proposed more efficient design for positron emission tomography called DirectPET, capable reconstructing multislice volumes (i.e., 16 400 400) sinograms. Approach: Large-scale direct neural accomplished by addressing the associated memory space challenge through introduction specially...

Direct reconstruction of positron emission tomography (PET) data using deep neural networks is a growing field research. Initial results are promising, but often the complex, memory utilization inefficient, produce relatively small 2-D image slices (e.g., 128 × 128), and low count rate reconstructions varying quality. This article proposes FastPET, novel direct convolutional network that architecturally simple, space efficient, works for nontrivial 3-D volumes capable processing wide...

This article presents and validates a newly developed GATE model of the Siemens Inveon trimodal imaging platform. Fully incorporating positron emission tomography (PET), single-photon computed (SPECT), (CT) data acquisition subsystems, this enables feasibility studies new applications, development reconstruction correction algorithms, creation baseline against which experimental results for real can be compared. Model validation was based on comparing simulation both empirical published...

Tomographic image reconstruction is often formulated as a regularized weighted least squares (RWLS) problem optimized by iterative algorithms that are either inherently algebraic or derived from statistical point of view. This paper compares modified version SIRT (Simultaneous Iterative Reconstruction Technique), which the former type, with SQS (Separable Quadratic Surrogates), latter type. We show two minimize same criterion function using similar forms preconditioned gradient descent....

Endpoint Detection and Response (EDR) systems play a crucial role in continuously monitoring endpoint activities to detect, analyze, respond cybersecurity threats real time. Traditional agent-based EDR rely on software agents installed endpoints for data collection, which can be impractical due the large number of devices, their mobility, privacy concerns. In contrast, agentless aim overcome these limitations by remotely collecting network host data, but they face challenges precise...

Cybersecurity researchers and security analysts rely heavily on data to train test network threat detection models, conduct post-breach forensic analyses. Comprehensive data-including traces, host telemetry, contextual information-are crucial for these tasks. However, widely used public datasets often suffer from outdated traffic features, statistical anomalies, simulation artifacts. Furthermore, existing collection systems frequently face architectural computational limitations,...

String alignment by dynamic programming is generalized to include cyclic shift and corresponding optimal cost for strings representing patterns. A guided search algorithm uses bounds on costs find all shifts. The are derived from submatrices of an initial matrix. Algorithmic complexity analyzed major stages in the search. applicability method illustrated with satellite DNA sequences circularly permuted protein sequences.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML"...

In conventional reconstruction of single photon emission computed tomography (SPECT) data acquired with a single-pinhole or multipinhole system, the point spread function (PSF) may be either approximated by some analytical equations substituted sensitivity function, which is integral PSF. We have developed method to numerically calculate PSF for pinhole system in order improve image resolution over sensitivity-function-based method. The calculates probability penetration through edges using...

Positron emission tomography (PET) scanners continue to increase sensitivity and axial coverage by adding an ever expanding array of block detectors. As they age, one or more detectors may lose due a malfunction component failure. The sinogram data missing as result thereof can lead artifacts other image degradations. We propose mitigate the effects malfunctioning carrying out repair using deep convolutional neural network. Experiments whole-body patient studies with varying amounts raw...

Partially saturated compacted-sand specimens were characterized by using three-dimensional (3D) image registration of dual-modal (neutron and X-ray) tomography data. Neutron X-ray imaging provide complementary information for precisely identifying the three phases (silica sand, air, water) a compacted sand specimen that is partially saturated. provides high contrast water phase, whereas silica phase due to different fundamental interaction mechanisms neutron with matters. interacts electron...

The paper describes a system for indoor scene modeling from sets of noisy laser range images. We address several important aspects thereof: preprocessing, which includes image segmentation and planar model fitting; view registration, is the method determining rigid transformation that relative pose camera platform between views; reconstruction, subsequent integration or fusion separate images into single 3D model. give an empirical analysis, demonstrates efficacy our plane-based registration...

The complexity and throughput of computer networks are rapidly increasing as a result the proliferation interconnected devices, data-driven applications, remote working. Providing situational awareness for requires monitoring analysis network data to understand normal activity identify abnormal activity. A scalable platform process visualize in real time large-scale enables security analysts researchers not only monitor study flow but also experiment develop novel analytics. In this paper,...

Describes how to estimate 3D surface models from dense sets of noisy range data taken different points view, i.e., multiple maps. The proposed method uses a sensor model develop an expression for the likelihood surface, conditional on set measurements. Optimizing this with respect parameters provides unbiased and efficient estimator. numerical algorithms make estimation computationally practical wide variety circumstances. results compare favorably state-of-the-art approaches that rely...

The mouse model of experimentally induced systemic AA amyloidosis is long established, well validated, and closely analogous to the human form this disease. However, induction amyloid by experimental inflammation unpredictable, inconsistent, difficult modulate. We have previously shown that murine deposits can be imaged using iodine-123 labeled SAP scintigraphy report here substantial refinements in both imaging technology itself. In regard, we generated a novel prototype which mice...

Abstract The Feldkamp algorithm is widely accepted as a practical conebeam reconstruction method for three‐dimensional x‐ray computed tomography. We introduce focus of attention, an effective and simple to implement datadriven preprocessing scheme, identifying convex subset voxels that include all those relevant the object under study. By concentrating on this during reconstruction, we reduce computational demands correspondingly. To achieve further speed‐up, computations are distributed...

Three-dimensional iterative reconstruction of high-resolution, circular orbit cone-beam x-ray CT data is often considered impractical due to the demand for vast amounts computer cycles and associated memory. In this paper, we show that computational burden can be reduced by limiting a small, well-defined portion image volume. We first discuss using support region defined set voxels covered all projection views. then present data-driven preprocessing technique called focus attention...

This paper describes a computational method using tensor math for higher order singular value decomposition (HOSVD) of registered images. Tensor is rigorous way to expose structure embedded in multidimensional datasets. Given dataset 2-D images, the represented format and HOSVD computed obtain set basis The images constitute linear original dataset. data-driven does not require user select parameters or assign thresholds. A specific application uses pixel-level fusion into single image...