Full Depth Image Research Articles

Improved dispersion-encoded full-range spectral interferometry for large depth, large inclination and rough samples.

In this study, we provide and validate an enhanced dispersion-encoded full-range spectral interferometry that offers improved measurement accuracy for samples characterized by significant depth, inclination, and roughness. Due to the low intensity of the optical signal in these samples, the optical signal is easy to be overwhelmed by the disturbance terms, demanding a more precise phase compensation. To address this issue, the direct current is removed by subtracting the envelope of the interference spectrum, allowing the weak signal near zero optical delay can be identified. Besides, considering the unwrapped phase error caused by the spectrometer aberrations, only the data with good phase continuity are preserved, which improves the accuracy of phase compensation. Using the proposed technique, the depth measurement range of the system is extended from 6 mm to 12 mm, while achieving an axial measurement precision of 2.5µm. In addition, the full-depth images of a ceramic standard step block and a 3D-printed sample are measured. It shows that our system exhibits superior adaptation to complex surfaces compared to the laser line profiler.

Fusion of NDE Scanning and Photogrammetric Data for Concrete Bridge Decks and Girders Condition Assessment

The first case history would present 3-D results of Impact Echo Scanning and Ground Penetrating Radar (GPR) Scanning plus Spectral Analyses of Surface Waves tests of post-tensioned concrete bridge girders. The NDE results were overlaid on photogrammetric images of visible corrosion/cracking damage to the concrete bridge girders of an aging bridge due to de-icing salts and a marine environment. Cart-based scanning with GPR and Impact Echo and Spectral Analyses of Surface Waves NDE methods is commonly being conducted of both bare concrete decks and asphalt overlaid decks to map both top and bottom delaminations and depth of concrete cover. The data is being used in conjunction with chlorides and carbonation testing of concrete cores to recommend repairs and evaluate remaining service lives for bridges. Photogrammetric images of bare concrete in particular are being used to visibly compare areas of spalling, delamination and deck patching for improved interpretation, visualization and mapping of internal deck delaminations and other concrete damage with this data fusion approach to provide more accurate surface and full-depth images of bridge deck conditions.

In situ process monitoring and automated multi-parameter evaluation using optical coherence tomography during extrusion-based bioprinting

In three-dimensional (3D) bioprinting, errors during the printing process leads to lower structural fidelity, and the desired structural and functional performances cannot be fully satisfied. Process monitoring with high-speed imaging techniques is helpful for identifying material deposition errors. 3D reconstruction of printed objects enables comprehensive evaluation of structural characteristics, with wide-field full-depth imaging being necessary for large objects. In this study, we demonstrate 3D extrusion-based bioprinter-associated optical coherence tomography (3D P-OCT) to achieve high-speed, wide-field and full-depth imaging, and provide in situ process monitoring and comprehensive evaluation for 3D bioprinting. In 3D P-OCT, a wide field was achieved with a lateral image mosaic using the simplified iterative closest point algorithm, and the extension of imaging depth was achieved with a longitudinal image mosaic using image fusion based on maximum intensity values. During the printing process, 3D P-OCT enables real-time multi-parameter quantification for intelligent feedback. In conclusion, with in situ process monitoring and evaluation, 3D P-OCT contributes to ensure better structural and functional performances of 3D functional tissue constructs.

Systematic ultrastructural comparison of swept-source and full-depth spectral domain optical coherence tomography imaging of diabetic macular oedema

Background/AimsOptical coherence tomography (OCT) is commonly used to diagnose and assess diabetic macular oedema (DME). Swept-source OCT (SS-OCT) promises improved imaging depth and more independence from media opacities. Heidelberg Spectralis...

Full-depth compressive sensing spectral-domain optical coherence tomography based on a compressive dispersion encoding method.

By combining the advantages of compressive sensing optical coherence tomography (OCT) and full-depth OCT in terms of imaging time and imaging depth, we demonstrate how compressive sampling and dispersion encoding can be simultaneously used to reconstruct a full-depth OCT image. Moreover, by considering the image processing speed, we propose a two-step compressive dispersion encoding (TCDE) method, in which a large dispersion imbalance is introduced between the reference arm and the sample arm and two iterations are performed. The first iteration selects the signals with higher intensity and then removes their conjugate items and incoherent aliasing artifacts caused by undersampling based on the least squares method. The second iteration selects the signals with lower intensity. Experimental results show that nearly the same conjugate inhibition ratio can be obtained with 50% sampled data and 100% sampled data using the TCDE method. Full-depth images of a glass slide, an onion, and a live fish eye are obtained from 50% and 100% sampled data using the TCDE method. For a 1.4 mm×3.6 mm fish eye image, the conjugate items are reduced by 33.2 and 31.7dB using 50% sampled data and 100% sampled data, respectively.

Full-depth spectral domain optical coherence tomography technology insensitive to phase disturbance.

To achieve full-depth spectral domain optical coherence tomography in the case of strong environmental disturbance, the iterative phase-shifting (IPS) method and modified dispersion-coded (MDC) method are proposed in this work. In IPS, the precise amount of phase shift is retrieved by iteration, and the direction of the phase shift is determined by dispersion compensation. Conjugate mirror items and noise can be simultaneously eliminated by two captured interferograms, whereas only one of them can be removed in the traditional phase-shift method with two interferograms. In MDC, they are removed through dispersion compensation and signal extraction with a single interferogram. Full-depth images of a glass slide, an onion, and a live fish eye are obtained by the two methods. The advantages and disadvantages of each method are analyzed and compared. IPS is found to be more effective for removing conjugate artifacts, whereas MDC is more conducive to real-time imaging. For a 2 mm × 3.6 mm image of a fish eye (200 depth scans and 1200 spectral sampling points per depth scan), the mirror image artifact is reduced by 28.55 dB in MDC and 41.53 dB in IPS. Processing times are 5.1 seconds (20 iterations) for the IPS method and 0.91 seconds for MDC.

Redefining 3Dimensional placental membrane microarchitecture using multiphoton microscopy and optical clearing

IntroductionRemodeling of human placental membranes (amniochorionic or fetalmembrane) throughout gestation, a necessity to accommodate increasing uterine volume, involves continuous alterations (replacement of cells and remodeling of extracellular matrix). Methodologic limitations have obscured microscopic determination of cellular and layer-level alterations. This study used a combination of advanced imaging by multiphoton autofluorescence microscopy (MPAM) and second harmonic generation (SHG) microscopy along with tissue optical clearing to characterize the 3Dimensional multilayer organization of placental membranes. MethodsPlacental membranes biopsies (6 mm) collected from term, not-in-labor cesarean deliveries (n = 7) were fixed in 10% formalin (native) or treated with 2,2′-thiodiethanol to render them transparent for deeper imaging. Native and cleared tissues were imaged using MPAM (cellular autofluorescence) and SHG (fibrillar collagen). Depth z-stacks captured the amnion epithelium, underlying matrix layers, and in the cleared biopsies, the decidua layer. ResultsMPAM and SHG revealed fetal membrane epithelial topography and collagen organization in multiple matrix layers. Term amnion layers showed epithelial shedding and gaps. Optical clearing provided full-depth imaging with improved visualization of collagen structure, mesenchymal cells in extracellular matrix layers, and decidua morphology. Layer thicknesses measured by imaging corroborated with histology. Mosaic tiling of MPAM/SHG image stacks allowed large area visualization of entire biopsies. ConclusionMPAM-SHG microscopy allowed for study of this multi-layered tissue and revealed shedding, gap formation, and other structural changes. This approach could be used to study structural changes associated with membranes as well as other uterine tissues to better understand events in normal and abnormal parturition.

SPITZER ULTRA FAINT SURVEY PROGRAM (SURFS UP). II. IRAC-DETECTED LYMAN-BREAK GALAXIES AT 6 ≲ z ≲ 10 BEHIND STRONG-LENSING CLUSTERS

ABSTRACT We study the stellar population properties of the IRAC-detected 6 ≲ z ≲ 10 galaxy candidates from the Spitzer UltRa Faint SUrvey Program. Using the Lyman Break selection technique, we find a total of 17 galaxy candidates at 6 ≲ z ≲ 10 from Hubble Space Telescope images (including the full-depth images from the Hubble Frontier Fields program for MACS 1149 and MACS 0717) that have detections at signal-to-noise ratios ≥ 3 in at least one of the IRAC 3.6 and 4.5 μm channels. According to the best mass models available for the surveyed galaxy clusters, these IRAC-detected galaxy candidates are magnified by factors of ∼1.2–5.5. Due to the magnification of the foreground galaxy clusters, the rest-frame UV absolute magnitudes M 1600 are between −21.2 and −18.9 mag, while their intrinsic stellar masses are between 2 × 108 M ⊙ and 2.9 × 109 M ⊙. We identify two Lyα emitters in our sample from the Keck DEIMOS spectra, one at z Lyα = 6.76 (in RXJ 1347) and one at z Lyα = 6.32 (in MACS 0454). We find that 4 out of 17 z ≳ 6 galaxy candidates are favored by z ≲ 1 solutions when IRAC fluxes are included in photometric redshift fitting. We also show that IRAC [3.6]–[4.5] color, when combined with photometric redshift, can be used to identify galaxies which likely have strong nebular emission lines or obscured active galactic nucleus contributions within certain redshift windows.

Hybrid Deep Network and Polar Transformation Features for Static Hand Gesture Recognition in Depth Data

Static hand gesture recognition is an interesting and challenging problem in computer vision. It is considered a significant component of Human Computer Interaction and it has attracted many research efforts from the computer vision community in recent decades for its high potential applications, such as game interaction and sign language recognition. With the recent advent of the cost-effective Kinect, depth cameras have received a great deal of attention from researchers. It promoted interest within the vision and robotics community for its broad applications. In this paper, we propose the effective hand segmentation from the full depth image that is important step before extracting the features to represent for hand gesture. We also represent the novel hand descriptor explicitly encodes the shape and appearance information from depth maps that are significant characteristics for static hand gestures. We propose hand descriptor based on Polar Transformation coordinate is called Histogram of Polar Transformation (HPT) in order to capture both shape and appearance. Beside a robust hand descriptor, a robust classification model also plays a very important role in the hand recognition model. In order to have a high performance in recognition rate, we propose hybrid model for classification based on Sparse Auto-encoder and Deep Neural Network. We demonstrate large improvements over the state-of-the-art methods on two challenging benchmark datasets are NTU Hand Digits and ASL Finger Spelling and achieve the overall accuracy as 97.7% and 84.58%, respectively. Our experiments show that the proposed method significantly outperforms state-of-the-art techniques.

Full Depth Imaging: neue Aufnahmetechnik mittels optischer Kohärenztomografie (OCT)

The aim of this study was to evaluate the full depth imaging (FDI) mode as a new acquisition technique with spectral domain (SD) optical coherence tomography (OCT) from Heidelberg Engineering for illustrating vitreoretinal and choroidal structures with high contrast. Patients with different diseases such as age-related macular degeneration, chorioretinopathia centralis serosa, diabetic retinopathy and epiretinal gliosis were examined with the FDI mode. For comparison, we also examined healthy probands with conventional OCT and the enhanced depth imaging (EDI) mode. FDI images were obtained with a manual acquisition technique. First, 100 conventional OCT scans of the vitreoretinal interface were averaged. After manual switching to the EDI mode the previous averaged image was overlayed with EDI images until vitreous, retina and choroid were projected in one comparably sharp image. The FDI mode enables SD-OCT images showing the vitreoretinal interface and deep choroid structures with a high contrast. The new acquisition mode has a few limitations: it is only possible to perform a single linear scan, a raster scan is not possible. The FDI mode is a manual acquisition technique and not automated yet. By a combination of averaged images of the vitreoretinal interface with the help of conventional SD-OCT scans with EDI OCT scans the FDI mode exhibits a simultaneous contrast image of the posterior vitreous, the retina and the choroid. Whereas the application of OCT was focused to evaluate the retina-retinal pigment epithel complex, the routine reinforcement of FDI scans could additionally show potential vitreous and choroidal pathologies. As the FDI mode is not an automated application yet it may be too complex to use for routine diagnostics at the moment.

Automated de-stacking using compact and low-cost robotized system

Purpose – This paper aims to introduce a compact and low-cost robotized system and corresponding processing method for automatically identifying and de-stacking circulation boxes under natural stacking status. Design/methodology/approach – The whole system is composed of an industrial robot, a laser scanner and a computer. Automated de-stacking requires comprehensive and accurate status information of each box. To achieve this goal, the robot carries the laser scanner to perform linear scanning to describe a full depth image for the whole working area. Gaussian filter is applied to the image histogram to suppress the undesired noise. Draining and flooding process derived from classic algorithm identifies each box region from an intensity image. After parameters calculation and calibration, the grasping strategy is estimated and transferred to the robot to finish the de-stacking task. Findings – Currently, without pre-defined stack status, there is still manual operated alignment in stacking process in order to enable automatic de-stacking using robot. Complicated multi-sensor system such as video cameras can recognize the stack status but also brings high-cost and poor adaptability. It is meaningful to research on the efficient and low-cost measurement system as well as corresponding common data processing method. Research limitations/implications – This research presents an efficient solution to automated de-stacking task and only tests for three columns stack depending on the actual working condition. It still needs to be developed and tested for more situations. Originality/value – Utilizing only single laser scanner to measure box status instead of multi-sensor is novel and identification method in research can be suitable for different box types and sizes.

Combined Depth Imaging Technique on Spectral-Domain Optical Coherence Tomography

To describe a technique to obtain combined images of vitreoretinal and choroidal structures using spectral-domain (SD) optical coherence tomography (OCT) and to evaluate applicability in normal eyes and limitations in eyes with cataract. Prospective, observational case series. Three different foveal scans, including conventional SD OCT, enhanced depth imaging OCT and the novel method called combined depth imaging (CDI) OCT, were obtained in 42 eyes of healthy volunteers and in 26 eyes with cataract using the Heidelberg Spectralis HRA (Heidelberg Engineering). The CDI OCT images were obtained manually using an image modification process that enhances the vitreoretinal interface first and then the choroid, while averaging 100 separate OCT scans. The visualization of the inner border of the preretinal pocket and the outer border ofthe choroid was graded by independent masked observers for each OCT scan method. The CDI technique was able to create a good-quality combined image of the posterior structures in all the eyes, including eyes with cataract. The agreement between the grading performed by the independent observers was high for both the inner border of the vitreal pocket (κ, 0.86; P < .001) and the outer choroidal border (κ, 0.90; P < .001). CDI OCT was equivalent to conventional SD OCT in visualizing the vitreal pocket (P= .445 for normal eyes, P= .162 for eyes with cataract) and was equivalent to enhanced depth imaging OCT in visualizing the outer choroidal border (P= .660 for normal eyes, P= .329 for eyes with cataract). CDI OCT was superior to conventional SD OCT and enhanced depth imaging OCT in visualizing both of the structures (P < .001). The manual technique of CDI OCT is highly sensitive to visualize posterior vitreoretinal and choroidal structures into a single full-depth image and is not affected by mild to moderate cataract.

Cumulative data acquisition in comparative photon-counting three-dimensional imaging

In recent years, time-correlated single-photon counting techniques have been applied to time-of-flight measurements for long-distance range-finding and depth imaging. Depth imaging has been performed by obtaining timing information from an individual single-photon detector and scanning the optical field to obtain a full depth image. Typically, the measurement is made by dwelling on each individual depth pixel for a pre-defined integration time and completing the data acquisition for that pixel before steering the beam to the adjacent spatial position. We present a novel photon-counting data acquisition mode where the time-of-flight histograms for each depth pixel are gradually populated. The system repeatedly scans the same spatial frame with short per-pixel dwell times, and sufficient photon statistics are built up over many frames by cumulating photon events from all acquired frames. The technique is used to compare the depth imaging performance of two single-photon avalanche diode detectors: a novel, resonant-cavity enhanced shallow-junction device; and a commercially available thick-junction device.

From time to depth imaging with ‘Beyond Dix’

In many parts of the world, pre-stack time migration (PSTM) still represents the majority of seismic imaging activity in the industry. The reason for this is the simple efficiency and robustness of time imaging and its ability to focus seismic reflectors for many geological settings. Limitations of PSTM appear in the case of strong lateral velocity variations, where the more rigorous imaging and more accurate velocity models offered by Pre-Stack Depth Migration (PSDM) are required. In areas of moderate complexity, where PSTM begins to struggle we introduce a new, accurate method, ‘Beyond Dix’, to help bridge the gap between PSTM and PSDM. Beyond Dix provides an accurate fast-track PSDM from PSTM outputs. It takes full advantage of the efficiency, good focusing, and high signal-to-noise ratio available from time imaging to jump-start the PSDM process. The name comes from the fact that we are going beyond the limitations of the 1D Dix inversion commonly used to derive depth interval velocities from the PSTM velocities. It uses the full kinematic information available in the time migrated domain to directly build an accurate depth velocity model and bypass the 1D Dix inversion altogether. Not only does this approach extract the maximum value from time imaging, it also adds great flexibility to imaging projects by allowing a seamless and fast transition from PSTM to PSDM and thus avoiding the need to choose at an early stage between a time or depth approach. It is clear that in addition to providing a fast-track PSDM, Beyond Dix has a range of possible applications, including building more accurate initial models for full depth imaging projects. In this paper we explain how the detailed information freely available within the time migrated domain can be used directly to build an accurate depth velocity model. We also illustrate the application of Beyond Dix with two examples from different geological settings. In particular, we demonstrate that the resulting PSDM images converted back to time exhibit significantly improved focusing and structural delineation compared to equivalent PSTM images. Depth velocity model building The estimation of an accurate 3D depth velocity model certainly remains one of the greatest challenges in seismic imaging. Depth velocity model building typically involves: N Initial PSDM N Residual moveout (RMO) picking on common image point (CIP) gathers N Structural dip picking in the migrated domain N Update of the depth velocity model by ray-based tomographic inversion Starting from an initial velocity model, an initial PSDM is performed to build CIP gathers for RMO picking. The objective of the velocity model building/update is to minimize the observed RMO (related to the velocity error) in the migrated domain, flattening the events on the CIP gathers. From the knowledge of the RMO and the structural dip one can implement a linearized solution to tomographically update the velocity model with the objective of reducing RMO in the next PSDM run (Al-Yahya, 1989; Liu and Bleistein, 1995). The tomography is usually repeated through several iterations to solve for complex non-linear effects. To avoid the extra delay involved in running a full PSDM and re-picking RMO and dip after each tomographic update iteration, Guillaume et al. (2001) proposed an efficient kinematic approach. This same kinematic approach is used by Beyond Dix.