Precise Registration Research Articles

Reflectance Spectrum and Birefringence of the Retinal Nerve Fiber Layer With Hypertensive Damage of Axonal Cytoskeleton.

PurposeGlaucoma damages the retinal nerve fiber layer (RNFL). This study used precise multimodal image registration to investigate the changes of the RNFL reflectance spectrum and birefringence in nerve fiber bundles with different degrees of axonal damage.MethodsThe reflectance spectrum of individual nerve fiber bundles in normal rats and rats with experimental glaucoma was measured from 400 to 830 nm and their birefringence was measured at 500 nm. Optical measurements of the same bundles were made at different distances from the optic nerve head (ONH). After the optical measurements, the axonal cytoskeleton of the RNFL was evaluated by confocal microscopy to assess the severity of cytoskeletal change.ResultsFor normal bundles, the shape of the RNFL reflectance spectrum and the value of RNFL birefringence did not change along bundles. In treated retinas, damage to the cytoskeleton varied within and across retinas. The damage in retinal sectors was subjectively graded from normal-looking to severe. Change of spectral shape occurred near the ONH in all sectors studied. This change became more prominent and occurred farther from the ONH with increased damage severity. In contrast, RNFL birefringence did not show change in normal-looking sectors, but decreased in sectors with mild and moderate damage. The birefringence of severely damaged sectors was either within or below the normal range.ConclusionsVarying degrees of cytoskeletal damage affect the RNFL reflectance spectrum and birefringence differently, supporting differences in the ultrastructural basis for the two optical properties. Both properties, however, may provide a means to detect disease and to estimate ultrastructural damage of the RNFL in glaucoma.

A protocol for registration and correction of multicolour STED superresolution images.

Multicolour fluorescence imaging by STimulated Emission Depletion (STED) superresolution microscopy with doughnut-shaped STED laser beams based on different wavelengths for each colour channel requires precise image registration. This is especially important when STED imaging is used for co-localisation studies of two or more native proteins in biological specimens to analyse nanometric subcellular spatial arrangements. We developed a robust postprocessing image registration protocol, with the aim to verify and ultimately optimise multicolour STED image quality. Importantly, this protocol will support any subsequent quantitative localisation analysis at nanometric scales. Henceforth, using an approach that registers each colour channel present during STED imaging individually, this protocol reliably corrects for optical aberrations and inadvertent sample drift. To achieve the latter goal, the protocol combines the experimental sample information, from corresponding STED and confocal images using the same optical beam path and setup, with that of an independent calibration sample. As a result, image registration is based on a strategy that maximises the cross-correlation between sequentially acquired images of the experimental sample, which are strategically combined by the protocol. We demonstrate the general applicability of the image registration protocol by co-staining of the ryanodine receptor calcium release channel in primary mouse cardiomyocytes. To validate this new approach, we identify user-friendly criteria, which - if fulfilled - support optimal image registration. In summary, we introduce a new method for image registration and rationally based postprocessing steps through a highly standardised protocol for multicolour STED imaging, which directly supports the reproducibility of protein co-localisation analyses. Although the reference protocol is discussed exemplarily for two-colour STED imaging, it can be readily expanded to three or more colours and STED channels.

All-passive pixel super-resolution of time-stretch imaging

Based on image encoding in a serial-temporal format, optical time-stretch imaging entails a stringent requirement of state-of-the-art fast data acquisition unit in order to preserve high image resolution at an ultrahigh frame rate — hampering the widespread utilities of such technology. Here, we propose a pixel super-resolution (pixel-SR) technique tailored for time-stretch imaging that preserves pixel resolution at a relaxed sampling rate. It harnesses the subpixel shifts between image frames inherently introduced by asynchronous digital sampling of the continuous time-stretch imaging process. Precise pixel registration is thus accomplished without any active opto-mechanical subpixel-shift control or other additional hardware. Here, we present the experimental pixel-SR image reconstruction pipeline that restores high-resolution time-stretch images of microparticles and biological cells (phytoplankton) at a relaxed sampling rate (≈2–5 GSa/s)—more than four times lower than the originally required readout rate (20 GSa/s) — is thus effective for high-throughput label-free, morphology-based cellular classification down to single-cell precision. Upon integration with the high-throughput image processing technology, this pixel-SR time-stretch imaging technique represents a cost-effective and practical solution for large scale cell-based phenotypic screening in biomedical diagnosis and machine vision for quality control in manufacturing.

A Hierarchical Framework Combining Motion and Feature Information for Infrared-Visible Video Registration.

In this paper, we propose a novel hierarchical framework that combines motion and feature information to implement infrared-visible video registration on nearly planar scenes. In contrast to previous approaches, which involve the direct use of feature matching to find the global homography, the framework adds coarse registration based on the motion vectors of targets to estimate scale and rotation prior to matching. In precise registration based on keypoint matching, the scale and rotation are used in re-location to eliminate their impact on targets and keypoints. To strictly match the keypoints, first, we improve the quality of keypoint matching by using normalized location descriptors and descriptors generated by the histogram of edge orientation. Second, we remove most mismatches by counting the matching directions of correspondences. We tested our framework on a public dataset, where our proposed framework outperformed two recently-proposed state-of-the-art global registration methods in almost all tested videos.

High-Precision Registration of Point Clouds Based on Sphere Feature Constraints.

Point cloud registration is a key process in multi-view 3D measurements. Its precision affects the measurement precision directly. However, in the case of the point clouds with non-overlapping areas or curvature invariant surface, it is difficult to achieve a high precision. A high precision registration method based on sphere feature constraint is presented to overcome the difficulty in the paper. Some known sphere features with constraints are used to construct virtual overlapping areas. The virtual overlapping areas provide more accurate corresponding point pairs and reduce the influence of noise. Then the transformation parameters between the registered point clouds are solved by an optimization method with weight function. In that case, the impact of large noise in point clouds can be reduced and a high precision registration is achieved. Simulation and experiments validate the proposed method.

Time synchronization of consumer cameras on Micro Aerial Vehicles

This article discusses the problem of time registration between navigation and imaging components on Micro Aerial Vehicles (MAVs). Accurate mapping with MAVs is gaining importance in applications such as corridor mapping, road and pipeline inspections or mapping of large areas with homogeneous surface structure, e.g. forests or agricultural fields. Therefore, accurate aerial control plays a major role in efficient reconstruction of the terrain and artifact-free ortophoto generation. A key prerequisite is correct time stamping of images in global time frame as the sensor exterior orientation changes rapidly and its determination by navigation sensors influence the mapping accuracy on the ground. A majority of MAVs is equipped with consumer-grade, non-metric cameras for which the precise time registration with navigation components is not trivial to realize and its performance not easy to assess. In this paper, we study the problematic of synchronization by implementing and evaluating spatio-temporal observation models of aerial control to estimate residual delay of the imaging sensor. Such modeling is possible through inclusion of additional velocity and angular rate observations into the adjustment. This moves the optimization problem from 3D to 4D. The benefit of this approach is verified on real mapping projects using a custom build MAV and an off-the-shelf camera.

P13. Spine SBRT: Benefit of Magnetic Resonance Imaging acquisition in treatment position and first results of Volumetric Modulated Arc Therapy dose plan

Purpose In stereotactic body radiotherapy (SBRT), high-gradient dose is delivered and target volumes have to be delineated precisely in order to avoid irradiation of healthy tissue. Magnetic Resonance Imaging (MRI) acquisition in treatment position allows same spine curvature reproduction and shows to be useful to delineate organs at risk such as spinal cord. The aim of this study is to report the benefit of setting out an imaging protocol optimized for SBRT planning and to present a Volumetric Modulated Arc Therapy (VMAT) methodology to treat spine metastasis. Material and methods Patient immobilization and positioning was first set up at the GE Healthcare Planning CT scan with dedicated thermo-plastic nets, supports and cushions. An MR compatible table was designed by Orfit Industries and approved for testing by Siemens Healthcare. The same patient’s immobilization devices were used at the MR scan to perform optimized imaging series to reproduce treatment position. At the 1.5T Siemens Aera MR scan, head and body ex coils were used and imaging sequences were optimized to account for the table and immobilization devices. Coronal 3D Turbo Spin Echo T2-weighted and T1-weighted (3D TSE T2-w and 3D T1-w TSE) had the same acquisition matrix size and field-of-view with 1.00 mm slice thickness, resulting in isotropic voxel size of 1.00 mm3. TR/TE were 1100 ms/132 ms (T2-w) and 400 ms/18 ms (T1-w), respectively. Gross Target Volume (GTV) was contoured as the visible lesion on CT scan or hyper-signal on MR images. Clinical Target Volume was delineated upon GTV location according to [1]. The Planning Target Volume was defined as CTV + 2 mm. An optimized PTV was created: PTV2 = [PTV { (medullary canal + (spinal cord + 3 mm))]. VMAT dose plans were performed with AAA algorithm (Eclipse v11), 6MV fields and 1 mm calculation grid. The prescription was 3 * 9 Gy on the median volume of the PTV2. We compared different methods to decrease the dose outside the PTV2 (NTO function (Normal Tissue Objective) vs; NTO automatic vs. rings). A second study was performed to compare different configurations: 2 coplanar 360° arcs (collimators 15°/345° or 100°/80°) and 4 coplanar 360° arcs (collimators 15°/345/100°/80°). Results There was no problem of registration on the spine curvature between CT and MR images thanks to the table and immobilization devices (Fig. 1A). Examples of MR/Planning CT registration with benefit for target volume and organs at risk delineation are illustrated on Fig. 1B. Different geometries of PTV were considered, when spinous process was involved, 4 arcs are needed to better conform the PTV and respect the dose to the spinal cord. Dose plans reach good coverage of PTV2 (95% PTV received 96.8% of the prescribed dose), maximum dose for PTV2 was 105%. For the spinal cord +2 mm, max dose was 19.85 Gy, V11.1 Gy = 0.64 cc and V18Gy Conclusion Optimized imaging protocol in RT treatment position allows high precision registration with planning CT scan for a better delineation of target volume and organs at risk. All dose planning simulations fulfilled [1] , [2] , [3] the international recommendations. Download : Download high-res image (342KB) Download : Download full-size image

Robot-assisted stereotactic laser ablation of residual epileptogenic focus in the setting of chronic low back pain

Introduction: stereotactic laser-induced thermal therapy (LItt) is a minimally invasive procedure used to ablate a variety of intracranial pathology including tumors, epileptogenic foci and radiation necrosis. Potential benefits of LItt over open resection include avoiding a large craniotomy and pain associated with this. case report: We present a 58-year-old male who originally presented 15 years prior with newonset seizures due to a low-grade astrocytoma in the left lateral temporal lobe. He underwent focal tumor resection at that time but continued to have seizures. the patient had a history of degenerative disease in the lumbar spine and had already undergone several surgeries in the past including a failed fusion. He presented to our center where video-electroencephalogram (vEEG) localized the ictal onset zone to the left mesial temporal lobe adjacent to the resection cavity. He was offered craniotomy and LItt therapy, and he elected to undergo LItt. robotic assistance was utilized and bone fiducials were implanted for precise registration and implantation. A laser cannula was placed in the appropriate location and the ictal onset zone was ablated with Mrthermometry. the patient required no additional

INTEGRATING SMARTPHONE IMAGES AND AIRBORNE LIDAR DATA FOR COMPLETE URBAN BUILDING MODELLING

A complete building model reconstruction needs data collected from both air and ground. The former often has sparse coverage on building façades, while the latter usually is unable to observe the building rooftops. Attempting to solve the missing data issues in building reconstruction from single data source, we describe an approach for complete building reconstruction that integrates airborne LiDAR data and ground smartphone imagery. First, by taking advantages of GPS and digital compass information embedded in the image metadata of smartphones, we are able to find airborne LiDAR point clouds for the corresponding buildings in the images. In the next step, Structure-from-Motion and dense multi-view stereo algorithms are applied to generate building point cloud from multiple ground images. The third step extracts building outlines respectively from the LiDAR point cloud and the ground image point cloud. An automated correspondence between these two sets of building outlines allows us to achieve a precise registration and combination of the two point clouds, which ultimately results in a complete and full resolution building model. The developed approach overcomes the problem of sparse points on building façades in airborne LiDAR and the deficiency of rooftops in ground images such that the merits of both datasets are utilized.

INTEGRATING SMARTPHONE IMAGES AND AIRBORNE LIDAR DATA FOR COMPLETE URBAN BUILDING MODELLING

Abstract. A complete building model reconstruction needs data collected from both air and ground. The former often has sparse coverage on building façades, while the latter usually is unable to observe the building rooftops. Attempting to solve the missing data issues in building reconstruction from single data source, we describe an approach for complete building reconstruction that integrates airborne LiDAR data and ground smartphone imagery. First, by taking advantages of GPS and digital compass information embedded in the image metadata of smartphones, we are able to find airborne LiDAR point clouds for the corresponding buildings in the images. In the next step, Structure-from-Motion and dense multi-view stereo algorithms are applied to generate building point cloud from multiple ground images. The third step extracts building outlines respectively from the LiDAR point cloud and the ground image point cloud. An automated correspondence between these two sets of building outlines allows us to achieve a precise registration and combination of the two point clouds, which ultimately results in a complete and full resolution building model. The developed approach overcomes the problem of sparse points on building façades in airborne LiDAR and the deficiency of rooftops in ground images such that the merits of both datasets are utilized.

REMOTELY-SENSED GLACIER CHANGE ESTIMATION: A CASE STUDY AT LINDBLAD COVE, ANTARCTIC PENINSULA

Abstract. This study builds on existing literature of glacier change estimation in polar regions and is a continuation of efforts aimed at unlocking the information encapsulated in archival aerial photography of Antarctic Peninsula glaciers. Historical aerial imagery acquired in 1957 over three marine-terminating glaciers at Lindblad Cove on the West Coast of Trinity Peninsula is processed to extract digital elevation models (DEMs) which are subsequently compared to DEMs generated from present day (2014) WorldView-2 satellite stereo-imagery. The new WorldView-2 images offer unprecedented sub-metre resolution of the Antarctic Peninsula and are explored here to facilitate improved registration and higher accuracy analysis of glacier changes. Unlike many studies, which focus on glacier fronts or only restricted regions of glaciers, this paper presents a complete coverage of elevation changes across the glacier surfaces for two of the studied glaciers. The study utilises a robust least squares matching technique to ensure precise registration of the archival and modern DEMs, which is applied due to lack of existing ground control in this remote region. This case study reveals that, while many glaciers in polar regions are reported as experiencing significant mass loss, some glaciers are stable or even demonstrate mass gain. All three glaciers reported here demonstrated overall mean increases in surface elevation, indicative of positive mass balance ranging from 0.6 to 5.8 metre water equivalent between 1957 and 2014.

REMOTELY-SENSED GLACIER CHANGE ESTIMATION: A CASE STUDY AT LINDBLAD COVE, ANTARCTIC PENINSULA

This study builds on existing literature of glacier change estimation in polar regions and is a continuation of efforts aimed at unlocking the information encapsulated in archival aerial photography of Antarctic Peninsula glaciers. Historical aerial imagery acquired in 1957 over three marine-terminating glaciers at Lindblad Cove on the West Coast of Trinity Peninsula is processed to extract digital elevation models (DEMs) which are subsequently compared to DEMs generated from present day (2014) WorldView-2 satellite stereo-imagery. The new WorldView-2 images offer unprecedented sub-metre resolution of the Antarctic Peninsula and are explored here to facilitate improved registration and higher accuracy analysis of glacier changes. Unlike many studies, which focus on glacier fronts or only restricted regions of glaciers, this paper presents a complete coverage of elevation changes across the glacier surfaces for two of the studied glaciers. The study utilises a robust least squares matching technique to ensure precise registration of the archival and modern DEMs, which is applied due to lack of existing ground control in this remote region. This case study reveals that, while many glaciers in polar regions are reported as experiencing significant mass loss, some glaciers are stable or even demonstrate mass gain. All three glaciers reported here demonstrated overall mean increases in surface elevation, indicative of positive mass balance ranging from 0.6 to 5.8 metre water equivalent between 1957 and 2014.

Molecular basis for photoreceptor outer segment architecture.

To serve vision, vertebrate rod and cone photoreceptors must detect photons, convert the light stimuli into cellular signals, and then convey the encoded information to downstream neurons. Rods and cones are sensory neurons that each rely on specialized ciliary organelles to detect light. These organelles, called outer segments, possess elaborate architectures that include many hundreds of light-sensitive membranous disks arrayed one atop another in precise register. These stacked disks capture light and initiate the chain of molecular and cellular events that underlie normal vision. Outer segment organization is challenged by an inherently dynamic nature; these organelles are subject to a renewal process that replaces a significant fraction of their disks (up to ∼10%) on a daily basis. In addition, a broad range of environmental and genetic insults can disrupt outer segment morphology to impair photoreceptor function and viability. In this chapter, we survey the major progress that has been made for understanding the molecular basis of outer segment architecture. We also discuss key aspects of organelle lipid and protein composition, and highlight distributions, interactions, and potential structural functions of key OS-resident molecules, including: kinesin-2, actin, RP1, prominin-1, protocadherin 21, peripherin-2/rds, rom-1, glutamic acid-rich proteins, and rhodopsin. Finally, we identify key knowledge gaps and challenges that remain for understanding how normal outer segment architecture is established and maintained.

Depth completion for kinect v2 sensor

Kinect v2 adopts a time-of-flight (ToF) depth sensing mechanism, which causes different type of depth artifacts comparing to the original Kinect v1. The goal of this paper is to propose a depth completion method, which is designed especially for the Kinect v2 depth artifacts. Observing the specific types of depth errors in the Kinect v2 such as thin hole-lines along the object boundaries and the new type of holes in the image corners, in this paper, we exploit the position information of the color edges extracted from the Kinect v2 sensor to guide the accurate hole-filling around the object boundaries. Since our approach requires a precise registration between color and depth images, we also introduce the transformation matrix which yields point-to-point correspondence with a pixel-accuracy. Experimental results demonstrate the effectiveness of the proposed depth image completion algorithm for the Kinect v2 in terms of completion accuracy and execution time.

Initial Results of an Acetabular Center Axis Registration Technique in Navigated Hip Arthroplasty with Deformed Acetabular Rims.

BackgroundIn cementless total hip arthroplasty, imageless computer-assisted navigation is usually used to register the anterior pelvic plane (APP). The accuracy of this method is influenced by the subcutaneous tissues overlying the registration landmarks. On the other hand, the acetabular center axis (ACA) is determined from the acetabular rim. Precise registration of the ACA is possible because of direct palpation using a pointer. Imageless navigation using the ACA usually targets patients with normal acetabular morphology. The aim of this study was to investigate the accuracy of imageless navigation using the ACA instead of the APP in patients with normal or deformed acetabular rims.MethodsThe intraoperative cup position was compared with that obtained from the postoperative computed tomography (CT) images in 18 cases.ResultsThe inclination angle derived from the navigation system was 3.4 ± 5.3 degrees smaller and the anteversion angle was 1.4 ± 3.1 degrees larger than those derived from the CT images.ConclusionThe inclination cup angle of the navigation system was significantly inferior to the true value, particularly in cases with large anterior osteophytes.

Sticky Projections-A Model-Based Approach to Interactive Shader Lamps Tracking.

Shader lamps can augment physical objects with projected virtual replications using a camera-projector system, provided that the physical and virtual object are well registered to each other. Precise registration and tracking has been a cumbersome and intrusive process in the past. In this paper, we present a new method for tracking complex-shaped physical objects interactively. In contrast to previous approaches our system is mobile and makes solely use of the projection of the virtual replication to track the physical object and "stick" the projection to it. Our method consists of two stages, a fast pose initialization based on structured light patterns and a non-intrusive frame-by-frame tracking based on features detected in the projection. During the tracking phase, a radiometrically corrected virtual camera view based on the current pose prediction is rendered and compared to the captured image. Matched features are triangulated providing a sparse set of surface points that is robustly aligned to the virtual model. The alignment transformation serves as an input for the new pose prediction. Detailed experiments including the evaluation of the overlay accuracy show that our approach can accurately and robustly track complex objects at interactive rates.

The Pose Estimation of Mobile Robot Based on Improved Point Cloud Registration

Due to GPS restrictions, an inertial sensor is usually used to estimate the location of indoor mobile robots. However, it is difficult to achieve high-accuracy localization and control by inertial sensors alone. In this paper, a new method is proposed to estimate an indoor mobile robot pose with six degrees of freedom based on an improved 3D-Normal Distributions Transform algorithm (3D-NDT). First, point cloud data are captured by a Kinect sensor and segmented according to the distance to the robot. After the segmentation, the input point cloud data are processed by the Approximate Voxel Grid Filter algorithm in different sized voxel grids. Second, the initial registration and precise registration are performed respectively according to the distance to the sensor. The most distant point cloud data use the 3D-Normal Distributions Transform algorithm (3D-NDT) with large-sized voxel grids for initial registration, based on the transformation matrix from the odometry method. The closest point cloud data use the 3D-NDT algorithm with small-sized voxel grids for precise registration. After the registrations above, a final transformation matrix is obtained and coordinated. Based on this transformation matrix, the pose estimation problem of the indoor mobile robot is solved. Test results show that this method can obtain accurate robot pose estimation and has better robustness.

A 3D GIS-based interactive registration mechanism for outdoor augmented reality system

Registering virtual objects with reference to their corresponding real-world objects plays a key role in augmented reality (AR) system. Although there have been a lot of work on using vision-based method to perform registration for indoor AR system, it is very difficult to apply such registration method for outdoor AR system due to the inability to modify the objects in outdoor environment and the huge range of working area. 3D Geographic Information System (GIS) is capable of providing an outdoor virtual geographic environment where users are located at, which may provide users with a corresponding virtual object for the one in the physical world. In this study, a 3D GIS-based registration mechanism is proposed for outdoor AR system. Specifically, an easy-use interactive method for precise registration was developed to improve the performance of the registration. To implement the registration mechanism, an outdoor AR system built upon 3D GIS was developed, named Augmented Reality Geographical Information System (ARGIS). ARGIS has the capability of performing precise registration in outdoor environment without using traditional vision tracking method, which thus enables users to arbitrarily manipulate the system. A prototype was developed to conduct experiment on the campus of Peking University, Beijing, China to test the proposed registration mechanism. The experiment shows that the developed registration mechanism is feasible and efficient in the outdoor environment. The ARGIS is expected to enrich the applications of outdoor AR system, including but not limited to underground facility mapping, emergency rescue and urban planning.

Tracking of Defects in Reinforced Concrete Bridges Using Digital Images

AbstractThis paper proposes a novel approach for the periodic detection of defects in concrete bridges based on a set of dimensionless metrics pertinent to fractal analysis of digital images. Visual inspection and image subtraction methods are generally used for the periodic comparison of structural conditions. However, such approaches, such as visual inspections, have been identified with several limitations, but they are time consuming processes and decisions are influenced by individual experiences. Likewise, image subtraction method requires image registration, which is a difficult process in achieving precise image registration for reliable outputs. This research uses fractal analysis of digital images to track surface defects by estimating their fractal dimensions. The results of the fractal analysis of concrete beams are compared with the results of spectral analysis which requires images to be translated from spatial domain to frequency domain. The proposed method successfully generates unique met...

A New Approach for Solving the Local Extreme Problem

Registration algorithm has a very important use value in medical image. To improve the registration accuracy and registration speed, this paper proposes a new image registration algorithm which is SAP algorithm. SAP combines the advantages of high registration accuracy of simulated annealing algorithm with fast registration speed of Powell algorithm. To make the accuracy higher and speed faster of algorithm, this paper made twice improvements about SAP algorithm. In order to evaluate the performance of new algorithm, this paper conduct experiments to compare the performance of Powell algorithm, SAP algorithm, The improved SAP algorithm for the first time, The improved SAP algorithm for the second time. The experimental results show that improved SAP algorithm for the second time has highest registration precision and fastest registration speed.