Coarse Scan Research Articles

Determination of the SO/PHI-HRT wavefront degradation using multiple defocused images

Context. The Polarimetric and Helioseismic Imager on board the Solar Orbiter mission (SO/PHI) offers refocusing capabilities to cope with the strongly varying thermal environment of the optical system along the spacecraft’s elliptical orbit. The series of images recorded during in-flight focus calibrations can be employed for phase diversity analyses. Aims. In this work we infer the wavefront degradation caused by the thermo-optical effects in the High Resolution Telescope (HRT) from images taken during the fine and coarse focus scans performed in the commissioning phase of the instrument. The difference between these two series of images are mainly related to the employed defocused step (smaller for the fine scans) and the signal-to-noise ratio (higher for the coarse scans). We use the retrieved wavefronts to reconstruct the original scene observed during the calibration of the instrument. Methods. We applied a generalized phase diversity algorithm that allowed us to use several images taken with different amounts of defocus to sense the wavefront degradation caused by the instrument. The algorithm also uses information from both the inferred wavefront and the series of images to restore the solar scene. Results. We find that most of the retrieved Zernike coefficients tend to converge to the same value when increasing the number of images employed for PD for both the fine and the coarse focusing scans. The restored scenes also show signs of convergence, and the merit function is minimized more as K increases. Apart from a defocus, the inferred wavefronts are consistent for the two datasets (λ/10 − λ/11). For the fine scan images, the quiet-sun contrast improves from 4.5% for the original focused image up to about 10%. For the coarse scan images, the contrast of the restored scene is as high as 11%.

Deep Learning Aided Two-Stage Multi-Finger Beam Training in Millimeter-Wave Communication

Agile and reliable alignment of transceiver beams is crucial to support high transmission rate in millimeter-wave (mmWave) communications. In this letter, a deep learning aided two-stage multi-finger beam training (DL-TSMBT) algorithm is proposed for beam alignment purpose. In the first stage, a multi-finger beam based coarse scanning strategy is proposed to take a limited number of initial measurements, which are then fed into a customized convolutional neural network for feature extraction and candidate beam selection. In the second stage, the candidate beams are further trained to refine the beam selection. Numerical results validate the effectiveness of the DL-TSMBT proposed and show that DL-TSMBT outperforms several state-of-the-art traditional beam training baselines and a data-driven wide-beam training baseline, both in terms of misalignment probability and achievable spectrum efficiency.

3-D Auxiliary Classifier GAN for Hyperspectral Anomaly Detection via Weakly Supervised Learning

Hyperspectral anomaly detection (AD) is important in Earth observation and remote sensing. However, the low spatial resolution of hyperspectral images, insufficient samples and lack of prior information limit the detection accuracy. To solve these problems, in this paper, we propose an auxiliary classifier generative adversarial network model based on a three-dimensional (3D) convolutional neural network named 3D AC-GAN. Firstly, the model is based on a 3D convolutional neural network design, with 3D tensors as samples. The network maintains valuable image spatial spectrum joint features to achieve good detection results. It can also generate sufficient samples to achieve dataset augmentation, solving the overfitting problem in GAN training. Secondly, we train the model with a weakly supervised method. The label of the samples is obtained through the coarse scanning method. Then, the AC-GAN is trained with the bootstrapping method to mitigate the impact of noise labels. The experimental results show that our proposed algorithm outperforms state-of-the-art AD algorithms.

Unambiguous Direction-of-Arrival Estimation for Improved Scanning Efficiency in Subarray-Based Hybrid Array

Hybrid antenna array consisting of analog subarrays provides a low-cost solution to achieving high beamforming gain in millimeter-wave/terahertz communication systems. For beam adjustment, beam scanning can be readily applied to find the line-of-sight (LoS) path. Conventionally, the beam scanning process is inefficient because the number of grids, together with the scanning period, has to be large to achieve high resolution. To improve the beam scanning efficiency, in this paper we propose an off-gird direction-of-arrival (DoA) estimation method utilizing unequal-sized subarrays. Specifically, we first provide a new solution to overcome the ambiguity problem, i.e., the hybrid antenna array may render the DoA estimate non-unique. That new solution is formed by designing the antenna numbers in the subarrays and can be easily combined with the beam scanning process. We then propose a three-stage beam scanning strategy. At the first stage, coarse scanning is applied to roughly steer the subarrays along the LoS path. At the second stage, a simple DoA estimator is employed to obtain the candidate DoAs. Finally, beam scanning is performed again on the candidate DoAs to obtain the final DoA estimate. Simulation results demonstrate that the proposed method can achieve higher DoA estimation accuracy in shorter scanning period than the conventional beam scanning method; and compared with existing methods developed for equal-sized subarrays, the proposed method is more robust against multi-path interference.

Adaptive Synthetic Aperture Radar (SAR) Imaging for Optimal Cross-Range Resolution and Image Quality in NDE Applications

An adaptive scanning algorithm is proposed for reducing scanning time associated with generating synthetic aperture radar (SAR) images, for nondestructive evaluation (NDE) applications, while preserving optimal cross-range resolution and image quality. The proposed method is based on the fact that optimum SAR cross-range resolution is target depth, synthetic aperture dimension, and scanning step size dependent. Hence, in the proposed method, the target properties, such as position and depth, are first estimated using an initial coarse scan of the scene of interest. Then, a localized dense scan is performed for obtaining optimal spatial resolution and image quality. During this procedure, the synthetic aperture dimension of the localized dense scan is adaptively increased (optimized) by reducing pixel-by-pixel image root-mean-square (rms) intensity difference between the images produced before and after each increment increase in the synthetic aperture dimension of the localized dense scan. At the same time, scanning step size is determined in a manner, which is related to the target depth in order to reduce scanning time and to insure obtaining (close to) optimal spatial sampling. Results of several illustrative measurements are provided by which the efficacy of the proposed method is demonstrated. The proposed algorithm, which mainly applies for imaging a localized flaw or a strong-scattering target in a relatively homogenous environment, is common in NDE applications and can be implemented using an automated and adaptive process.

A Two-Step Readout Technique for Large-Array Resistive Sensors

Large-array resistive sensors have nowadays found various applications in a variety of medical and industrial systems. In this paper, a two-step readout procedure is proposed, which increases the average speed of the readout for the input patterns, located in an area much smaller than the entire array. In the proposed method, during the first step, only a spatially coarse scan is performed where the location of the input is roughly estimated. Then, during the second step, the values of the resistors are accurately measured, just within the allocated area. Measurement results of a $52\times 44$ resistive array used in a plantar pressure scanner show that the average readout time for a gait pattern is reduced from 23 ms for the conventional circuit to 5.7 ms using the proposed technique.

Frequency–Wavenumber Analysis of Deep Learning-based Super Resolution 3D GPR Images

This paper proposes a frequency–wavenumber (f–k) analysis technique through deep learning-based super resolution (SR) ground penetrating radar (GPR) image enhancement. GPR is one of the most popular underground investigation tools owing to its nondestructive and high-speed survey capabilities. However, arbitrary underground medium inhomogeneity and undesired measurement noises often disturb GPR data interpretation. Although the f–k analysis can be a promising technique for GPR data interpretation, the lack of GPR image resolution caused by the fast or coarse spatial scanning mechanism in reality often leads to analysis distortion. To address the technical issue, we propose the f–k analysis technique by a deep learning network in this study. The proposed f–k analysis technique incorporated with the SR GPR images generated by a deep learning network makes it possible to significantly reduce the arbitrary underground medium inhomogeneity and undesired measurement noises. Moreover, the GPR-induced electromagnetic wavefields can be decomposed for directivity analysis of wave propagation that is reflected from a certain underground object. The effectiveness of the proposed technique is numerically validated through 3D GPR simulation and experimentally demonstrated using in-situ 3D GPR data collected from urban roads in Seoul, Korea.

Development of an Automatic Localization System of Magnetic Particles for Hyperthermia Therapy

Magnetic hyperthermia is a promising cancer therapy gaining great interest in recent years. In this therapy, in addition to magnetic particles, important elements include techniques for detecting the position and temperature of magnetic particles in a tumor region in determining the effectiveness of therapeutic heating. In previous studies, we developed a low invasive heating and wireless temperature measurement system for magnetic hyperthermia using a ferromagnetic implant with low Curie temperature (FILCT). To make this approach feasible in clinical settings, a challenge remains when the FILCT injected into the tumor region deviates from the central axis of drive coil. As a result, the heating efficiency of FILCT and the temperature measurement accuracy of FILCT decrease. In this study, we develop an automatic localization system for magnetic particles. Using the constructed system, it was possible to automatically locate the position of magnetic particles with an accuracy below 1 mm in vitro by operating magnetic field supply and detection (MFSD) unit in two modes of coarse scanning (rotary scanning) and fine-tuned scanning (linear scanning) based on three pickup voltages induced in three pickup coils symmetrically installed inside drive coil.

Clinical Development and Evaluation of Megavoltage Topogram for Fast Patient Alignment on Helical Tomotherapy

PurposeTo develop and evaluate a fast patient localization tool using megavoltage (MV)-topogram on helical tomotherapy. Methods and MaterialsEighty-one MV-topogram pairs for 18 pelvis patients undergoing radiation were acquired weekly under an institutional review board–approved clinical trial. The MV-topogram imaging protocol requires 2 orthogonal acquisitions at static gantry angles of 0 degrees and 90 degrees for a programed scan length. A MATLAB based in-house software was developed to reconstruct the MV-topograms offline. Reference images (digitally reconstructed topograms, digitally reconstructed topograms) were generated using the planning computed tomography and tomotherapy geometry. The MV-topogram based alignment was determined by registering the MV-topograms to the digitally reconstructed topogram using bony landmark on commercial MIM software. The daily shifts in 3 translational directions determined from MV-topograms were compared with the megavoltage computed tomography (MVCT) based patient shifts. Linear-regression and two one-sided tests equivalence tests were performed to investigate the relation and equivalence between the 2 techniques. Seventy-eight MV-topogram pairs for 19 head and neck patients were included to validate the finding. ResultsThe magnitudes of alignment differences of (MVCT − MV-topogram) (and standard deviations) were −0.3 ± 2.1, −0.8 ± 2.4, and 1.6 ± 1.7 mm for pelvis and 0.6 ± 1.2, 0.8 ± 4.2, 1.6 ± 2.6 mm for head and neck; the linear-regression coefficients between 2 imaging techniques were 1.18, 1.10, 0.94, and 0.86, 0.63, 0.38 in the lateral, longitudinal, vertical directions for pelvis and head and neck, respectively. The acquisition time for a pair of MV-topograms was up to 12.7 times less than MVCT scans (coarse scan mode) while covering longer longitudinal length. ConclusionsMV-topograms showed equivalent clinical performance to the standard MVCT with significantly less acquisition time for pelvis and H&N patients. The MV-topogram can be used as an alternative or complimentary tool for bony landmark-based patient alignment on tomotherapy.

Detection and Inspection Planning for Ship Propeller Blades via Spectral Shape Analysis

Abstract Inline quality control for one-off or few off manufacturing requires highly accurate and automated 3D measurement systems. This paper presents an approach to the planning of robotic inspection of geometric tolerances for large ship propeller blades cast in NiAl bronze. The spectral shape of the blade is analyzed and compared to a generic propeller blade model so that the blade’s position and orientation in the scene can be determined. The shape analysis relies on the eigenspectrum of a Laplace-Beltrami operator for segmenting the scene and identifying the propeller blade. To avoid time-consuming inspection of the entire propeller blade, the foil sections of the blade are extracted from an initial coarse scanning of the scene. Then the identified foil sections are the basis for generating inspection view poses for a robot inspecting the propeller blade with a high accuracy 3D camera. The system is successfully validated in simulations and on experimental data.

Adaptive Single-Mode Fiber Coupling Method Based on Coarse-Fine Laser Nutation

One of the major restrictions of the free-space optical communication systems is the limitation of single-mode fiber (SMF) coupling efficiency that impacts the system performance. In this paper, an adaptive coupling method for optical communication system based on coarse-fine laser nutation technique was presented. The scanning strategy and algorithm were set up and experimentally examined. The experimental results demonstrate that the coarse-fine laser nutation technique is capable of achieving a good coupling efficiency even the beam spot and the SMF do not coincide with each other at the start. The SMF center calculation accuracy of coarse and fine scanning stage were 0.25 and 0.01 μ m, respectively. And the average coupling efficiency of the system can increase from 0.351 in open loop to 0.624 in closed loop under a simulated atmospheric turbulence condition, the offset compensation error was 0.1245 μ m when turbulence induced. Finally, some factors influencing the systems were also discussed.

Delamination localization in wind turbine blades based on adaptive time-of-flight analysis of noncontact laser ultrasonic signals

In this study, a two-level scanning strategy for a noncontact laser ultrasonic measurement system is proposed to expedite the inspection of a wind turbine blade. First, coarse scanning of the entire blade is performed with a low spatial resolution for initial delamination localisation. Then, dense scanning with a high spatial resolution is performed only within the identified delaminated region for delamination visualization. This study especially focuses on the initial delamination localisation using adaptive coarse scanning. Laser ultrasonic responses from two pitch-catch paths, names inspection pairs, are obtained within a specified coarse scanning grid. Then, potential delamination locations within the given grid are estimated through time-of-flight analysis of delamination reflected waves. Once potential delamination locations are estimated, new inspection pairs are placed near the potential locations for precise localisation. These steps are repeated for every coarse scanning grids on the target wind turbine blade. The feasibility of the proposed technique for rapid delamination detection is demonstrated with a 10 kW glass fibre reinforced plastic wind turbine blade.

Elemental bioimaging and speciation analysis for the investigation of Wilson's disease using μXRF and XANES.

A liver biopsy specimen from a Wilson's disease (WD) patient was analyzed by means of micro-X-ray fluorescence (μXRF) spectroscopy to determine the elemental distribution. First, bench-top μXRF was utilized for a coarse scan of the sample under laboratory conditions. The resulting distribution maps of copper and iron enabled the determination of a region of interest (ROI) for further analysis. In order to obtain more detailed elemental information, this ROI was analyzed by synchrotron radiation (SR)-based μXRF with a beam size of 4 μm offering a resolution at the cellular level. Distribution maps of additional elements to copper and iron like zinc and manganese were obtained due to a higher sensitivity of SR-μXRF. In addition to this, X-ray absorption near edge structure spectroscopy (XANES) was performed to identify the oxidation states of copper in WD. This speciation analysis indicated a mixture of copper(i) and copper(ii) within the WD liver tissue.

Globally consistent registration of terrestrial laser scans via graph optimization

In this paper we present a framework for the automatic registration of multiple terrestrial laser scans. The proposed method can handle arbitrary point clouds with reasonable pairwise overlap, without knowledge about their initial orientation and without the need for artificial markers or other specific objects. The framework is divided into a coarse and a fine registration part, which each start with pairwise registration and then enforce consistent global alignment across all scans. While we put forward a complete, functional registration system, the novel contribution of the paper lies in the coarse global alignment step. Merging multiple scans into a consistent network creates loops along which the relative transformations must add up. We pose the task of finding a global alignment as picking the best candidates from a set of putative pairwise registrations, such that they satisfy the loop constraints. This yields a discrete optimization problem that can be solved efficiently with modern combinatorial methods. Having found a coarse global alignment in this way, the framework proceeds by pairwise refinement with standard ICP, followed by global refinement to evenly spread the residual errors.The framework was tested on six challenging, real-world datasets. The discrete global alignment step effectively detects, removes and corrects failures of the pairwise registration procedure, finally producing a globally consistent coarse scan network which can be used as initial guess for the highly non-convex refinement. Our overall system reaches success rates close to 100% at acceptable runtimes <1h, even in challenging conditions such as scanning in the forest.

Source Number Detection and Realization of ROC for Spectrum Sensing in Cognitive Radio

Background/Objectives: The pre-assigned spectrum allocation policy that has been adopted by various wireless technologies according to the standards of Federal Communications Commission (FCC), in Cognitive radio, the whole available spectrum is grouped into many different bands and the usage of bands by different applications leads to the existence of spectrum hole(s). Methods/Statistical Analysis: High sampling rate is required for cognitive transceiver spectrum sensing applications, multiple analog front-end circuitry, high resolution of Analog to Digital Converters having large and dynamic range, and fast signal processors. Calculating the interference temperature or noise variance over intended Narrow Band (NB) transmission signals is a part of spectrum sensing. Findings: The main issue related to cognitive radio applications is to sense the vacant spectrum holes and simultaneously accommodate the unlicensed secondary users in that. For cognitive radio implementation, spectrum sensing is the foremost concern. The paper presents the realization of Receiver Operating Characteristic (ROC) for implementation of proposed source number detection for existing adaptive energy detection scheme. The realization is mapped using comprehensive Monte Carlo simulations that are quantified for detection performance as a received signal to noise ratio. Application/Improvements: As per the application point of view, different combinations of the sensing techniques are required for different requirements. For example, in case of quick and coarse scan of broad frequency range, the sensing method can of energy detection type. The present white spaces can further be discovered accurately using feature detection method.

SU‐E‐J‐51: The Impact of Off‐Center Position On Image Quality of Megavoltage CT

PurposeTo quantify the impact of off‐center position on image quality of megavoltage CT in head and neck tumor patient and body tumor patient.MethodsA Catphan 600 phantom and a Cheese phantom were imaged by TomoHD at the center and off‐center positions stepped by 5cm in AP and LR directions until the phantom edge approaching the imaging edge with fine, normal and coarse scan modes. Both phantoms incorporate image uniformity module, spatial resolution module and CT number linearity module. The CT number linearity module of Cheese phantom was set to simulate Catphan 600 phantom in a larger size. According to AAPM TG‐148 report, noise, image uniformity, spatial resolution and CT number variation were assessed for MVCT image quality. Centers of peripheral ROIs for noise and uniformity were about 4cm from phantom edge.ResultsNoise in all positions was within the criteria except the peripheral regions for Cheese phantom at off‐center scan positions. Image uniformity for most positions was acceptable, and all failed data were from the ROIs near imaging edge area. Spatial resolution degraded with off‐center scanning, and scan mode also made it worse with wider slice thickness, but just 1 level at most. CT number change with and without image uniformity correction for all positions were all less than tolerance, but it was close to the red line for water‐equivalent material.ConclusionThis work indicates that if depth of lesions is below 4cm and MVCT are used for dose calculations, the ipsilateral body edge should be 5cm within imaging edge. Otherwise, image uniformity should be concerned.

Enhancing Manual Scan Registration Using Audio Cues

Abstract. Indoor mapping and modelling requires that acquired data be processed by editing, fusing, formatting the data, amongst other operations. Currently the manual interaction the user has with the point cloud (data) while processing it is visual. Visual interaction does have limitations, however. One way of dealing with these limitations is to augment audio in point cloud processing. Audio augmentation entails associating points of interest in the point cloud with audio objects. In coarse scan registration, reverberation, intensity and frequency audio cues were exploited to help the user estimate depth and occupancy of space of points of interest. Depth estimations were made reliably well when intensity and frequency were both used as depth cues. Coarse changes of depth could be estimated in this manner. The depth between surfaces can therefore be estimated with the aid of the audio objects. Sound reflections of an audio object provided reliable information of the object surroundings in some instances. For a point/area of interest in the point cloud, these reflections can be used to determine the unseen events around that point/area of interest. Other processing techniques could benefit from this while other information is estimated using other audio cues like binaural cues and Head Related Transfer Functions. These other cues could be used in position estimations of audio objects to aid in problems such as indoor navigation problems.

Feature-Specific CT Measurements for Log Scanning: Theory and Application

Computed Tomography (CT) is extensively used as a medical diagnostic tool, and increasingly adopted for scientific and industrial research. In the wood industry, there is a growing interest in using the CT technique to assess the quality of logs entering a sawmill to enable the material to be appropriately processed into maximum value products. Internal features of interest include knots, heartwood/sapwood boundary, rot and splits. Most commercially available CT scanning systems are modeled on medical designs and provide high spatial and density resolution. They are very complex and delicate devices with correspondingly high cost. However, log scanning has its own distinctive characteristics: specific overall and feature geometries and relatively coarse scanning resolution requirement. To fit these characteristics, the novel geometry-based coarse-resolution CT scanning approach described here has been developed and implemented. The models, algorithms, scanner design and result validation are presented in detail. The resulting CT reconstructions for an example log using the proposed geometry-based coarse-resolution approach compare well with CT reconstructions for same log using the same data with conventional filtered back projection inversion. The good comparison gives confidence in the usefulness and applicability of the proposed CT method for industrial use in sawmills for log quality assessment.

Estimate of the secondary cancer risk from megavoltage CT in tomotherapy

We have assessed the radiation-induced excess cancer risk to organs from megavoltage computed tomography (MVCT). MVCT was performed in coarse, normal and fine scanning modes. Using a glass dosimeter, we measured the primary and the secondary doses inside a homemade phantom and at various distances from the imaging center. The organ-specific excess absolute risk (EAR) for cancer induction was estimated using an organ-equivalent dose (OED) based on the measured imaging doses. The average primary doses inside the phantom for the coarse, normal and fine scanning modes were 0.78, 1.15 and 2.15 cGy, respectively. The average secondary dose per scan, measured 20 to 60 cm from the imaging center, ranged from 0.044 to 0.008 cGy. The EAR for major organs indicated that when 30 MVCT scans are performed to position each patient during the course of radiation treatment, organ-specific cancers may develop in as many as 6 per 10,000 persons per year.

Ultrasonic Imaging System Based on Virtual Instrument

An imaging system of ultrasonic detection is presented for non-destructive testing (NDT) of complex structures by using virtual instrument technology. The control devices for C-scan as well as for imaging system are designed and manufactured. In the coarse scan mode with the scan step of 1 mm, the system can quickly give an image display of a cross section of 80 mm (L) ×60 mm (D) by one measurement. In the refined scan model, the system can show a refine image of the coin. All experiments on coin, bulk metal, and other forms of specimen verify the efficiency of the proposed method. The experimental results are accurate and reliable.