Low Backscatter Research Articles

OPTICAL COHERENCE TOMOGRAPHY (OCT) CHARACTERISTICS AND IMAGE ANALYSIS FOR IN-STENT RESTENOSIS USING SUPERVISED MACHINE LEARNING TECHNIQUES

Despite advancements in stent technology and PCI techniques, in-stent restenosis (ISR) remains a concern. OCT provides an ample amount of data to characterize mechanisms of ISR. Multiple studies showed poor correlation between OCT findings and histological findings in pathological specimen studies. The purpose of this study is to characterize the OCT morphological features of ISR to neo-atherosclerosis (NA) versus neo-intimal hyperplasia (NI) and then study the utility of automated tools for identification of these plaque morphologies. All patients with ISR and OCT image obtained at the QEII health science center in Halifax were included in our study. All OCT images were analysed visually according to homogeneousity, back scatter and lumen characteristics by an expert observer and the mechanism of ISR were categorized as NA vs. NI. Subsequently, image analysis and RGB coding, using imaging software along with supervised machine learning tools, was utilized to test different classification algorithms and predictive models for ISR mechanism. For the purpose of this study we only selected patients characterized as having NA vs. NI as pathogenesis for ISR by visual assessment and compared them to the classification according to automated supervised machine learning. A total of 60 patients with OCT images available for analysis. 48 patients visually characterized with NA or NI were included in this analysis. There was significant difference between the groups in terms of tissue characteristics with 50% of plaques in NI are homogeneous versus 3.6% in NA (P= 0.001). High backscatter occurred in 100% of NI, but there was low backscatter in 78% of NA. Lumen shape was mainly regular in NI compared to irregular in NA (100% versus 14.3% p < 0.000). Plaque rupture was present in 64.3% of NA. There was no significant difference between of the groups in terms of diabetes, hypertension or dyslipidemia. However, there were more current smokers in the NA cohort compared to NI (57% versus 20% P=0.01). Using supervised machine learning techniques, tissue characteristics, backscatter and lumen shape were predictive for the pathogenesis of ISR with 97.9% accuracy. The positive predictive value for the model was 95% for NA versus 100% for NI. There are distinct morphological characteristics for pathogenesis of ISR. These distinct characteristics could be used as predictive models for identification of ISR pathogenesis. Future studies and validation are needed to determine whether automated imaging techniques may help predict the long-term outcomes for ISR with various treatments, according to tissue type.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

Acoustic reflectivity of a harbor porpoise (Phocoena phocoena).

Acoustic backscatter measurements were conducted on a stationary harbor porpoise (Phocoena phocoena) under controlled conditions. The measurements were made with the porpoise in the broadside aspect using three different types of signals: (1) a 475 μs linear frequency-modulated (FM) pulse with a frequency range from 23 to 160 kHz; (2) a simulated bottlenose dolphin (Tursiops "truncates") click with a peak frequency of 120 kHz; and (3) a simulated killer whale (Orcinus orca) click with a peak frequency of 60 kHz. The measurement with the FM pulse indicated that the mean target strength at the broadside aspect decreased from -26 to -50 dB as the frequency increased from 23 to 120 kHz in a nearly linear fashion (on a logarithm plot). Target strength variation with frequency was similar to a previous backscatter measurement on a bottlenose dolphin over a comparable frequency range (23-80 kHz). The porpoise seems to be a stealth body with low backscatter properties. The target strength of the porpoise was also about 15-16 dB lower than that of the bottlenose dolphin. The difference in lung volume of the two species when expressed in dB was also approximately 15 dB.

FLOOD DETECTION IN NORWAY BASED ON SENTINEL-1 SAR IMAGERY

Abstract. After large flood incidents in Norway, The Norwegian Water Resources and Energy Directorate (NVE), has the responsibility for documenting the flooded areas. This has so far mainly been performed by utilising aerial images and visual interpretation. Satellite images are a valuable source of additional information as they are able to cover vast areas in each satellite pass. In this paper a fully automated system for detecting and delineating floods with the use of Synthetic Aperture Radar (SAR) images from the Sentinel-1 satellites is presented. In SAR images wet areas and water bodies usually show lower backscatter than dry areas. The flood detection system is thus based on comparing a reference image acquired before the flood with the flood event image. A Sentinel-1 training dataset has been obtained and manually annotated by NVE from three flood events in Norway. This training set has been used to train a random forest (RF) classifier, which outputs a score for each pixel in the SAR image. This score image is thresholded in order to obtain a crude flood detection. Unfortunately, changes in the backscatter may also be triggered by other events such as melting snow and harvested fields of crops. To mitigate such lookalikes, several techniques have been implemented and tested. This includes masking based on size, slope and height above nearest drainage (HAND). The experiments presented show that the system performance is very good. Of the 179 manually labelled flood objects, 168 are detected. The system is being applied operationally at NVE.

Ovda Fluctus, the Festoon Lava Flow on Ovda Regio, Venus: Not Silica‐Rich

AbstractOvda Fluctus (6.1°S, 95.5°E) is a lava flow complex on the equatorial tessera highlands of Ovda Regio, Venus. We examined its morphology and geologic setting to determine if its apparent emplacement rheology is consistent with silica‐rich (e.g., rhyolitic) lava; this has significant implications for the compositions of Venus's tesserae. Using Magellan radar data, we find that the radar properties (emissivity, roughness, and backscatter) of Ovda Fluctus are similar to those of the surrounding tessera, although the flow is smoother at multiple scales. Ovda Fluctus is a “festoon flow complex,” whose surface is rumpled into arcuate folds. The flow includes multiple flow lobes and at least two distinct flow units. The flow complex includes a portion at high altitude (~5 km above mean planetary radius) that has low radar backscatter and high radar emissivity compared with lower‐altitude portions of the complex. The high‐altitude region of Ovda Fluctus is continuous with the lower‐elevation portions: the change in radar properties does not represent different flows. Outlines of Ovda Fluctus flow lobes have fractal dimensions consistent with basaltic pahoehoe lavas. The margin of Ovda Fluctus is at significantly higher elevation than its center, a characteristic seen in basalt flows on Earth, but not on more silica‐rich flows. Thus, the available evidence suggests that Ovda Fluctus had an emplacement rheology consistent with a basaltic composition; this result provides no support for hypotheses that Ovda Regio (a highlands tessera terrain) is composed of granitic rock.

Orthogonal beam ballistic backscatter stimulated Raman microscopy.

When the axial gain length of a stimulated Raman microscope is less than about 40% of the emission wavelength significant dipole-like ballistic backscatter will occur. Here we analyze a scanning microscope configured with orthogonal water dipping pump and probe objectives that satisfies this criterion. The pump beam focus may be a Gaussian spot or a droplet Bessel beam which minimizes the secondary Bessel beam lobes and provides multiple simultaneous pump focal spot regions. Radial and linearly polarized pump beams enable backscattered polarized signals along both transverse axes of the probe beam. Low level Mie backscatter is the primary photon noise source which should enable rapid sub-wavelength resolution 3-dimensional imaging of label-free Raman contrast for in-vivo pathology, as well as, imaging physiologic concentrations of Raman labelled metabolites and drugs.

Adjustment of the dual frequency altimeter low subsection backscatter coefficient statistical model

Adjustment of the dual frequency altimeter low subsection backscatter coefficient statistical model

Continuous Fading Suppression Method for Φ-OTDR Systems Using Optimum Tracking Over Multiple Probe Frequencies

The demand for distributed acoustic sensors, which are capable of reconstructing the amplitude, frequency, and phase of an acoustic field, is increasing. These sensors are typically realized by phase-sensitive optical time-domain reflectometry (Φ-OTDR). However, common Φ-OTDR systems suffer from a fading phenomenon, which causes amplitude fluctuation on Rayleigh backscattering traces, and the scattered light may not have enough intensity in some regions. These areas have low amplitude backscattering that may be even lower than the system noise floor during some periods of time. Therefore, we cannot reconstruct the phase signal properly in such low intensity areas. Systems with multiple frequencies have been proposed to achieve fading suppression. However, online data processing of such schemes remains a challenge, especially for continuous in-field applications. Prediction of fading must be performed in real time. Any delay caused by massive calculations is not acceptable. In this paper, a continuous fading suppression method based on a Φ-OTDR system with three different probe frequencies is presented as well as a tracking algorithm for selecting the optimum probe signal for any time, which predicts the occurrence of fading before it actually occurs. The performance of the proposed method has been experimentally evaluated and statistically analyzed. The distortion induced by the fading effect could be suppressed to 1.15% under continuous real-time running. The method is highly effective and repeatable, which makes it suitable for practical online purposes.

Detector performance and defect densities in CdZnTe after two-step annealing

Defects both microscale and nanoscale are play an important role in CdZnTe (CZT) device performance. Typical micro-scale defects such as Te inclusions were removed via a two-step annealing process, and their concentration was analyzed via IR transmission microscopy. In addition, transmission electron microscopy (TEM) measurement was employed to investigate the evolution of nano-scale defects after the annealing process. Dislocation and stacking faults were commonly observed defects in as-grown and annealed CZT. The line shape defects, which are possibly related to the stress field around dislocations, disappeared during the in-situ the annealing at 200–220 °C. A Frisch-grid CZT detector made via the two-step annealing process exhibited improved energy resolution and low backscattering counts in Cs-137 gamma spectra.

Active Mode Single Pixel Imaging in the Highly Turbid Water Environment Using Compressive Sensing

Underwater imaging has always been a challenge due to limitations imposed by scattering and absorption nature of the underwater environment. The light would be highly degraded after reflection and propagation in the water medium. Being an advanced imaging technique, Single-pixel Imaging (SPI) is applicable to acquire object spatial information in low light, severe backscattering, and high absorption conditions. Combination of Compressive Sensing (CS) and SPI can overcome the limitation of SPI algorithms such as long data-acquisition time, low reconstruction efficiency and poor reconstruction quality. In the current research, an underwater SPI system based on CS is established to reconstruct our two-dimensional (2D) transparent object. We have systematically investigated the influence of water turbid degree, measurement pattern types and number of measurements on image reconstruction performance. The proposed system is capable to reconstruct the object even when the turbidity reaches up to 80 Nephelometric Turbidity Unit (NTU), where the conventional imaging systems are unusable. Proposed reconstruction method in our research can save more than 70% data acquisition time, compared to SPI algorithm. Our experimental setup has been compared to a conventional imaging system and an underwater ghost imaging system to show its efficiency in obtaining accurate results from turbid water conditions. Furthermore, various algorithm comparison and imaging enhancement studies demonstrates that our algorithm is superior in bringing highly convex optimization at a faster rate with a smaller number of measurements. This work creates new insight into the SPI application and generates a guideline for researchers to improve their applications.

On the analysis of a time series of X–band TerraSAR–X SAR imagery over oil seepages

ABSTRACTA large time series of 42 dual–polarimetric co–polarized TerraSAR-X (TSX) StripMap Synthetic Aperture Radar (SAR) measurements are exploited to monitor a well-known oil seep area, i.e., the Taylor Energy site in the Gulf of Mexico. A comprehensive scattering analysis is undertaken to assess the impact of SAR imaging parameters (polarization, angle of incidence – AOI, noise floor) and environmental conditions (wind speed – WS, oil properties) on single-polarization SAR–based sea oil seep observation. The main goal of this study is to evaluate the reliability of the scattering–based information derived from the time series of TSX SAR imagery. A two-scale backscattering model is considered to give a physical framework that supports a better understanding of the effects of the above–mentioned factors.Experimental results showed that the high TSX noise floor significantly limits a reliable interpretation of the slick–free sea surface and oil seep backscattering at AOIs larger than 34 and 26, respectively, since they are contaminated by noise. Hence, it is shown that, at larger AOIs, the joint contribution of noisy SAR measurements and low oil backscattering does not result in a larger oil/sea separability. The latter is not remarkably influenced by polarization and WS, under low–to–moderate conditions. Experiments also demonstrate that, when reliable SAR measurements are available, sea oil seep backscattering is affected by the oil’s damping properties more than its concentration in the water column. The time variability of the polluted area is also estimated using the time series of TSX imagery and the obtained results agree with independent analysis undertaken on the same test site.

Imaging of hidden object using passive mode single pixel imaging with compressive sensing

Hidden object imaging has always been challenging for obtaining satisfiable imaging because of the limitations caused by the reflections from the surrounding environment. The light is highly degraded after propagation and reflection from the hidden object. Single-pixel imaging (SPI) is an advanced imaging approach becoming more remarkable; applicable for acquiring spatial information in low light, high absorption and backscattering conditions. Combination of SPI and compressed sensing (CS) can efficiently tackle the key drawbacks of SPI, such as long data-acquisition time and low reconstruction resolution. In the present study, a CS based hidden object SPI system is designed. This is able to reconstruct an image without the influence of diffuse reflection from a two-dimensional (2D) target, which is placed in a corner practically concealing the objects over 10 × 10 cm of hidden space. The reconstruction obtained by our method is desirable and can save more than half of the data-acquisition time compared to the SPI algorithm. Our contribution presents a new insight for the application of SPI and provides a guideline for researchers to improve their applications.

Development of a Tissue-Mimicking Phantom of the Brain for Ultrasonic Studies

Constructing tissue-mimicking phantoms of the brain for ultrasonic studies is complicated by the low backscatter coefficient of brain tissue, causing difficulties in simultaneously matching the backscatter and attenuation properties. In this work, we report on the development of a polyvinyl alcohol-based tissue-mimicking phantom with properties approaching those of human brain tissue. Polyvinyl alcohol was selected as the base material for the phantom as its properties can be varied by freeze–thaw cycling, variations in concentration and the addition of scattering inclusions, allowing some independent control of backscatter and attenuation. The ultrasonic properties (including speed of sound, attenuation and backscatter) were optimized using these methods with talc powder as an additive. It was determined that the ultrasonic properties of the phantom produced in this study are best matched to brain tissue in the frequency range 1–3 MHz, indicating its utility for laboratory ultrasonic studies in this frequency range.

The role of lake size and local phenomena for monitoring ground-fast lake ice

ABSTRACTIn this study, we assess the effect of the lake size on the accuracy of a threshold-based classification of ground-fast and floating lake ice from Sentinel-1 Synthetic Aperture Radar (SAR) imagery. For that purpose, two new methods (flood-fill and watershed method) are introduced and the results between the three classification approaches are compared regarding different lake size classes for a study area covering most of the Yamal Peninsula in Western Siberia. The focus is on April, the stage of maximum lake ice thickness, for the years 2016 and 2017. The results indicate that the largest lakes are likely most prone to errors by the threshold classification. The newly introduced methods seem to improve classification results. The results also show differences in fractions of ground-fast lake ice between 2016 and 2017, which might reflect differences in temperatures between the winters with severe impact on wildlife and freshwater fish resources in the region. Patterns of low backscatter responsible for the classification errors in the centre of the lakes were investigated and compared to the optical Sentinel-2 imagery of late-winter. Strong similarities between some patterns in the optical and SAR data were identified. They might be zones of thin ice, but further research is required for clarification of this phenomenon and its causes.

Mapping High Mountain Lakes Using Space-Borne Near-Nadir SAR Observations

Near-nadir interferometric imaging SAR (Synthetic Aperture Radar) techniques are promising in measuring global water extent and surface height at fine spatial and temporal resolutions. The concept of near-nadir interferometric measurements was implemented in the experimental Interferometric Imaging Radar Altimeters (InIRA) mounted on Chinese Tian Gong 2 (TG-2) space laboratory. This study is focused on mapping the extent of high mountain lakes in the remote Qinghai–Tibet Plateau (QTP) areas using the InIRA observations. Theoretical simulations were first conducted to understand the scattering mechanisms under near-nadir observation geometry. It was found that water and surrounding land pixels are generally distinguishable depending on the degree of their difference in dielectric properties and surface roughness. The observed radar backscatter is also greatly influenced by incidence angles. A dynamic threshold method was then developed to detect water pixels based on the theoretical analysis and ancillary data. As assessed by the LandSat results, the overall classification accuracy is higher than 90%, though the classifications are affected by low backscatter possibly from very smooth water surface. The algorithms developed from this study can be extended to all InIRA land measurements and provide support for the similar space missions in the future.

Impact of low tissue backscattering by optical coherence tomography on endothelial function after drug-eluting stent implantation.

This study evaluated the impact of optical coherence tomography (OCT)-derived low-backscattered tissue on mid-term coronary endothelial function after drug-eluting stent (DES) implantation. Although OCT enables detailed in vivo evaluation of neointimal tissue characterization after DES implantation, its association with physiological vascular healing response is unclear. Thirty-three stable angina pectoris patients underwent OCT examination and endothelial function testing with intracoronary infusion of incremental doses of acetylcholine 8-month after DES implantation in a single lesion of the left anterior descending artery. Neointimal tissue was classified into two patterns based on the predominant OCT light backscatter: high backscatter and low backscatter. Although the presence of uncovered or malapposed stent strut was not associated with the degree of vasoconstriction, the degree of vasoconstriction was significantly greater in the DES with low-backscattered neointima than in the DES without low-backscattered neointima (- 32.1 ± 25.7 vs. - 4.1 ± 20.1%, p = 0.003). Moreover, there was an inverse linear relationship between low backscatter tissue index and degree of vasoconstriction after acetylcholine infusion (r = 0.50 and p = 0.003). The endothelium-dependent vasomotor response after 8-month of DES was impaired in patients with low neointimal tissue backscatter on OCT imaging. OCT assessment of low-backscattered tissue may be used as surrogate markers for impairment of endothelial function after DES.

Quality difference of neointima following the implantation of everolimus-eluting bioresorbable scaffolds and metallic stents in patients with ST-elevation myocardial infarction: quantitative assessments by light intensity, light attenuation, and backscatter on optical coherence tomography in the TROFI II trial

We aimed to assess possible differences in neointimal quality after everolimus-eluting bioresorbable scaffold (BVS) implantation in comparison with cobalt-chromium everolimus-eluting scaffold (CoCr-EES) implantation by optical frequency domain imaging (OFDI). This study is a post hoc analysis of the TROFI II trial assessing neointimal quality six months after the implantation of BVS (N=82) and CoCr-EES (N=87) in STEMI patients. Neointimal light property analysis by OFDI fully automatically computed light attenuation, backscatter and light intensity for superficial and deep neointima. High light attenuation/backscatter and high light intensity are reportedly associated with lipidic change and tissue maturation, respectively. Superficial and deep neointima in BVS presented lower light attenuation than CoCr-EES (superficial: 0.77±0.15 vs. 1.27±0.55 mm-1, p<0.001; deep: 0.88±0.20 vs. 1.17±0.27 mm-1, p<0.001). Superficial neointima in BVS showed comparable backscatter to that of CoCr-EES (4.81±0.52 vs. 4.94±0.61, p=0.141), while deep neointima in BVS showed lower backscatter than that of CoCr-EES (4.60±0.62 vs. 4.97±0.62, p<0.001). Light intensity of superficial neointima was comparable between both arms (139±13 vs. 144±30, p=0.236), whereas light intensity of deep neointima in BVS was lower than CoCr-EES (129±14 vs. 138±21, p<0.001). The present OFDI comparison suggested that tissue maturation was comparable but lipidic change of neointima was less prominent after BVS than after CoCr-EES implantation.

Detection of Stones in Marine Habitats Combining Simultaneous Hydroacoustic Surveys

Exposed stones in sandy sublittoral environments are hotspots for marine biodiversity, especially for benthic communities. The detection of single stones is principally possible using sidescan-sonar (SSS) backscatter data. The data resolution has to be high to visualize the acoustic shadows of the stones. Otherwise, stony substrates will not be differentiable from other high backscatter substrates (e.g., gravel). Acquiring adequate sonar data and identifying stones in backscatter images is time consuming because it usually requires visual-manual procedures. To develop a more efficient identification and demarcation procedure of stone fields, sidescan sonar and parametric echo sound data were recorded within the marine protected area of “Sylt Outer Reef” (German Bight, North Sea). The investigated area (~5.900 km2) is characterized by dispersed heterogeneous moraine and marine deposits. Data from parametric sediment echo sounder indicate hyperbolas at the sediment surface in stony areas, which can easily be exported. By combining simultaneous recorded low backscatter data and parametric single beam data, stony grounds were demarcated faster, less complex and reproducible from gravelly substrates indicating similar high backscatter in the SSS data.

Ultrafast Surface State Spin-Carrier Dynamics in the Topological Insulator Bi_{2}Te_{2}Se.

Topological insulators are promising candidates for optically driven spintronic devices, because photoexcitation of spin polarized surface states is governed by angular momentum selection rules. We carry out femtosecond midinfrared spectroscopy on thin films of the topological insulator Bi_{2}Te_{2}Se, which has a higher surface state conductivity compared to conventionally studied Bi_{2}Se_{3} and Bi_{2}Te_{3}. Both charge and spin dynamics are probed utilizing circularly polarized light. With a sub-band-gap excitation, clear helicity-dependent dynamics is observed only in thin (<20 nm) flakes. On the other hand, such dependence is observed for both thin and thick flakes with above-band-gap excitation. The helicity dependence is attributed to asymmetric excitation of the Dirac-like surface states. The observed long-lasting asymmetry over 10ps even at room temperature indicates low backscattering of surface state carriers which can be exploited for spintronic devices.

Flood Detection in PolSAR Images Based on Level Set Method Considering Prior Geoinformation

This letter presents a novel flood detection approach using full polarimetric synthetic aperture radar (PolSAR) images based on a level set method considering prior geoinformation. The prior geoinformation includes information derived from vector data and topography data. The main approach accomplishes flood detection by the improved level set method, an active contour segmentation model, based on the classical Wishart distribution. Vector data are used to generate the zero initial level set curves. To investigate the separability between water and nonwater low–backscattering objects in PolSAR images, topography information is incorporated into the level set function as a constraint. Moreover, we introduce a piecewise statistical method to refine the result with the Kullback–Leibler divergence of circular polarization coherence. In addition, we design a new quantitative evaluation index to assess flood detection results. For validation, three real PolSAR images of flooded area are tested. The experimental results confirm the effectiveness of the proposed method.

THE LOW BACKSCATTERING OBJECTS CLASSIFICATION IN POLSAR IMAGE BASED ON BAG OF WORDS MODEL USING SUPPORT VECTOR MACHINE

Abstract. Due to the forward scattering and block of radar signal, the water, bare soil, shadow, named low backscattering objects (LBOs), often present low backscattering intensity in polarimetric synthetic aperture radar (PolSAR) image. Because the LBOs rise similar backscattering intensity and polarimetric responses, the spectral-based classifiers are inefficient to deal with LBO classification, such as Wishart method. Although some polarimetric features had been exploited to relieve the confusion phenomenon, the backscattering features are still found unstable when the system noise floor varies in the range direction. This paper will introduce a simple but effective scene classification method based on Bag of Words (BoW) model using Support Vector Machine (SVM) to discriminate the LBOs, without relying on any polarimetric features. In the proposed approach, square windows are firstly opened around the LBOs adaptively to determine the scene images, and then the Scale-Invariant Feature Transform (SIFT) points are detected in training and test scenes. The several SIFT features detected are clustered using K-means to obtain certain cluster centers as the visual word lists and scene images are represented using word frequency. At last, the SVM is selected for training and predicting new scenes as some kind of LBOs. The proposed method is executed over two AIRSAR data sets at C band and L band, including water, bare soil and shadow scenes. The experimental results illustrate the effectiveness of the scene method in distinguishing LBOs.