Automatic Image Alignment Research Articles

Size photometry and fluorescence imaging of immobilized immersed extracellular vesicles.

Immunofluorescence analysis of individual extracellular vesicles (EVs) in common fluorescence microscopes is gaining popularity due to its accessibility and high fluorescence sensitivity; however, EV number and size are only measurable using fluorescent stains requiring extensive sample manipulations. Here we introduce highly sensitive label-free EV size photometry (SP) based on interferometric scattering (iSCAT) imaging of immersed EVs immobilized on a glass coverslip. We implement SP on a common inverted epifluorescence microscope with LED illumination and a simple 50:50 beamsplitter, permitting seamless integration of SP with fluorescence imaging (SPFI). We present a high-throughput SPFI workflow recording >10,000 EVs in 7min over ten 88×88µm2 fields of view, pre- and post-incubation imaging to suppress background, along with automated image alignment, aberration correction, spot detection and EV sizing. We achieve an EV sizing range from 37 to ∼220nm in diameter with a dual 440 and 740nm SP illumination scheme, and suggest that this range can be extended by more advanced image analysis or additional hardware customization. We benchmark SP to flow cytometry using calibrated silica nanoparticles and demonstrate superior, label-free sensitivity. We showcase SPFI's potential for EV analysis by experimentally distinguishing surface and volumetric EV dyes, observing the deformation of EVs adsorbed to a surface, and by uncovering distinct subpopulations in <100nm-in-diameter EVs with fluorescently tagged membrane proteins.

Automatic image alignment and stitching for ultrasound-based robotic inspection of complex geometry components

Robotic inspection of complex geometry components using immersion ultrasonic techniques is relevant for many ultrasonic Non-Destructive Testing (NDT) applications in different industries. To image large component, ultrasonic probe is manipulated around the component immersed in water using a robotic guided system to create a tiled image of the entire component. Due to the mechanical vibrations of the high-speed robotic arm, the probe position coordinates provided by the robotic system are not precise enough to ensure an accurate reconstruction (stitching) of a composite image from all individual images. In this work, we propose a stitching method specifically designed to create a single 2D image of the surface of an inspected component from a stack of Total Focusing Method (TFM) images. This stitching method uses Iterative Closest Point (ICP) registration to estimate a 2D rigid transformation between two consecutive 2D images, by maximizing the overlap between the surface geometries extracted from each image. The capabilities of this imaging technique are illustrated by various simulated and experimental results carried out in a water tank. Significant improvements in surface image quality, leading to accurate surface reconstruction, are shown for vertical vibrations with displacements of more than two operating wavelengths and for rotational vibrations with deviation angles of less than 1°. The results also show that the resolving power of the ICP algorithm decreases for strong rotational vibrations.

MULTI-SATELLITE IMAGE ALIGNMENT OVER LARGE AREAS WITH FEATURELESS REGIONS

Abstract. There is a great deal of interest in fusing together the information provided by different satellites for real-time change detection on the surface of the earth. For detecting important types of changes on the ground, it is necessary to inject geometry into the data provided by low-res satellites using multi-view imaging satellites that record each point on the ground from multiple perspectives. Combining these perspectives and generating a DSM (Digital Surface Model) gives us the geometry needed for a more meaningful analysis of satellite data. Before such an analysis can be carried out, it is necessary to align the images from all available satellites. Automatic image alignment, however, requires features on the ground that can be identified and correctly matched across different images using computer vision algorithms. While such features are common in urban areas, that is not always the case in predominantly rural areas that present a more-or-less uniform texture to the sensors. In this paper we present methods for automatic identification and alignment of featureless regions. Featureless regions are identified using point spread maps, which are a byproduct of DSM generation. The subsequent strategy for aligning featureless regions depends on the proportion of featureless regions to feature-rich regions. If most of the AOI (Area of Interest) is feature-rich, we ignore featureless regions when estimating inter-satellite image alignment parameters and apply those parameters to the entire AOI. Finally, we present a technique to propagate and fuse parameters from feature-rich regions to featureless regions.

The Principle and State-of-art Applications for CT Detector

Contemporarily, significant progress has been made in the development and application of image fusion technology in the field of diagnostic imaging. Image fusion is a fully automated image alignment and interpretation system that not only allows images with different characteristics to be displayed, interpreted, compared, and analyzed on the same platform, but also provides a fast and seamless pathway to clinical diagnosis and treatment. The purpose of this study was to explore the imaging theory, clinical advantages and limitations of CT. At the beginning of the study, the definition and development history of CT will be explained. Subsequently, in addition to imaging theory and key parameters, one can also understand the individual advantages and clinical application of CT. Afterwards, the limitations of CT will be mentioned, and the new technology of PET/CT will be introduced. As the most advanced medical imaging technology, PET/CT has improved the way of single PET and CT scanning, making them more widely used, making it the best combination of medical imaging and diagnostic technology. Overall, these results shed light on guiding further exploration of CT.

En face Ultrawidefield OCT of the Vortex Vein System in Central Serous Chorioretinopathy

To investigate whether noninvasive en face ultrawidefield (UWF) OCT can demonstrate salient features of the choroidal vasculature in eyes with central serous chorioretinopathy (CSC). Retrospective observational case series. Patients diagnosed with CSC who underwent UWF indocyanine green angiography (ICGA) and widefield OCT imaging were included. Widefield OCT imaging was performed with a horizontal 23-mm× vertical 20-mm field of view of 5 visual fixations (1 central and 4 peripheral fixations) to compose structural en face UWF OCT montage images and UWF choroidal thickness maps. Automated image alignment was performed before grading. A comparison of choroidal vascular findings seen with UWF ICGA and en face UWF OCT images, including size and distribution of choroidal venous drainage areas and identification of dilated choroidal veins (pachyvessels) crossing the physiologic choroidal watershed zones. The spatial correlation between choroidal vascular hyperpermeability on UWF ICGA images and areas of choroidal thickening on UWF choroidal thickness maps was determined. Forty-two eyes from 27 patients with CSC with a mean age of 56 ± 12 years (range, 31-77 years) were included. Quantitative measures of vortex vein drainage areas on en face UWF OCT images were significantly and positively correlated with those obtained with UWF ICGA (mean Pearson r= 0.825, P < 0.01). Identification of pachyvessels crossing the choroidal watershed zones showed an excellent correlation between UWF ICGA and en face UWF OCT images (mean Spearman ρ= 0.873, P < 0.01). In all cases, choroidal vascular hyperpermeability was observed on UWF ICGA spatially colocalized with areas of choroidal thickening on the UWF choroidal thickness map. Congestion within the entire drainage area of the dominant vortex systems was observed on UWF choroidal thickness maps. In eyes with CSC, noninvasive en face UWF OCT imaging can show distinctive features of choroidal venous insufficiency previously identified with UWF ICGA. Ultrawidefield OCT choroidal thickness maps enable quantitative assessment of choroidal congestion. Proprietary or commercial disclosure may be found after the references.

QDM[formula omitted]: A MATLAB toolbox for analyzing quantum diamond microscope (QDM) magnetic field maps

Paleomagnetic measurements of rock magnetizations are typically performed using classical net moment rock magnetometers on bulk, millimeter- to centimeter-sized samples. In this case, the limited spatial resolution effectively averages across the signal of multiple populations of magnetic grains, each of which may have a distinct geological history. Magnetic field imaging with the quantum diamond microscope (QDM) allows for the measurement of weakly magnetic (10−16 Am2) samples at micrometer spatial resolution, potentially isolating the signal of magnetic grain populations and resolving ambiguities from bulk sample analyses. To achieve such high resolution, the QDM retrieves the energy spectrum of nitrogen–vacancy (NV) color centers within micrometer-scale pixels across a millimeter-scale field of view. Therefore, large amounts of data need to be processed to generate a magnetic field map, which itself often requires further specialized analysis. Until now, no freely-available, comprehensive, open-source software package existed that was able to process this type of data. Here we give an overview of the most important features of QDMlab, our open-source MATLAB toolbox for generating and analyzing QDM magnetic field maps of geologic samples. QDMlab utilizes modern computational techniques like graphics processing unit (GPU) and spectral fitting routines as well as automated image alignment algorithms. QDMlab contains easy-to-use functions for (1) generating magnetic field maps from raw QDM data, (2) map editing, and (3) quantifying the net magnetic moment and rock magnetic properties of rock and mineral samples.

Automated Image Alignment for Comparing Microvascular Changes Detected by Fluorescein Angiography and Optical Coherence Tomography Angiography in Diabetic Retinopathy

ABSTRACT PURPOSE To quantitatively compare microvascular features in the macula of patients with diabetic retinopathy (DR) using fluorescein angiography (FA) and optical coherence tomography angiography (OCTA). METHODS Patients with DR were recruited from the Cairo University Hospital. FA was performed using a Topcon TRC-50DX or Heidelberg Spectralis HRA+OCT. OCTA was performed using an Optovue RTVue-XR Avanti. FA images were cropped and aligned to the corresponding OCTA images using i2k Align Retina software. The foveal avascular zone (FAZ), area of ischemia, and microaneurysms (MAs) were manually quantified using ImageJ. The fractal dimension (FD) was calculated from each skeletonized image using the FracLac plugin of ImageJ after retinal vascular segmentation. RESULTS Twenty-four eyes of 17 patients were evaluated, but only 18 eyes were successfully aligned. There was no difference in FAZ area measured for FA and OCTA images. Compared with OCTA images, FD was significantly less for FA images (1.66 ± 0.048 versus 1.72 ± 0.023, p < .001). Significantly more MAs were identified on FA images (102 ± 27.5) compared with OCTA (47.5 ± 11.7, p < .0001). The number of MAs on FA correlated with decreasing best corrected visual acuity (r2 = 0.315, p = .015) and increasing central macular thickness (r2 = 0.492, p = .001). No such associations were found with MAs detected on OCTA. Nevertheless, the area of ischemia in the FA images (8.5 ± 4.1%) was significantly smaller compared with the area measured in both the superficial (30.7 ± 9.5%) and deep capillary plexus (21.6 ± 10.9%) of the OCTA (p < .001). Interestingly, number of MAs in the FA images correlated with increasing area of ischemia in the FA (r2 = 0.568, p < .001) but only the superficial segment of the depth-resolved OCTA scans (r2 = 0.539, p < .001). CONCLUSIONS OCTA is a non-invasive tool capable of resolving the retinal vasculature in greater detail when compared with FA but detects significantly fewer MAs. Automatic alignment facilitates quantitative comparison of the microvascular features in DR.

3D HIGH-QUALITY MODELING OF SMALL AND COMPLEX ARCHAEOLOGICAL INSCRIBED OBJECTS: RELEVANT ISSUES AND PROPOSED METHODOLOGY

Abstract. 3D modelling of inscribed archaeological finds (such as tablets or small objects) has to consider issues related to the correct acquisition and reading of ancient inscriptions, whose size and degree of conservation may vary greatly, in order to guarantee the needed requirements for visual inspection and analysis of the signs. In this work, photogrammetry and laser scanning were tested in order to find the optimal sensors and settings, useful to the complete 3D reconstruction of such inscribed archaeological finds, paying specific attention to the final geometric accuracy and operative feasibility in terms of required sensors and necessary time. Several 3D modelling tests were thus carried out on four replicas of inscribed objects, which are characterized by different size, material and epigraphic peculiarities. Specifically, in relation to photogrammetry, different cameras and lenses were used and a robust acquisition setup, able to guarantee a correct and automatic alignment of images during the photogrammetric process, was identified. The focus stacking technique was also investigated. The Canon EOS 1200D camera equipped with prime lenses and iPad camera showed respectively the best and the worst accuracy. From an overall geometric point of view, 50 mm and 100 mm lenses achieved very similar results, but the reconstruction of the smallest details with the 50 mm lens was not appropriate. On the other hand, the acquisition time for the 50 mm lens was considerably lower than the 100 mm one. In relation to laser scanning, the ScanRider 1.2 model was used. The 3D models produced (in less time than using photogrammetry) clearly highlight how this scanner is able to reconstruct even the high frequencies with high resolution. However, the models in this case are not provided with texture. For these reasons, a robust procedure for integrating the texture of photogrammetry models with the mesh of laser scanning models was also carried out.

Three-dimensional computer-assisted dissection of pancreatic lymphatic anatomy on human fetuses: a step toward automatic image alignment.

Pancreatic cancer is the fourth cause of death by cancer worldwide. Lymph node (LN) involvement is known to be the main prognostic factor. However, lymphatic anatomy is complex and only partially characterized. The aim of the study was to study the pancreatic lymphatic system using computer-assisted anatomic dissection (CAAD) technique and also to update CAAD technique by automatizing slice alignment. We dissected three human fetuses aged from 18 to 34 WA. 5-µm serial sections of duodeno-pancreas and spleen blocks were stained (hematoxylin-eosin, hematoxylin of Mayer and Masson trichrome), scanned, aligned and modeled in three dimensions. We observed a rich, diffuse but not systematized lymphatic network in the peri-pancreatic region. There was an equal distribution of LNs between the cephalic and body-tail portions. The lymphatic vascularization appeared in continuity from the celiac trunk to the distal ends of its hepatic and splenic arterial branches parallel to the nerve ramifications of the celiac plexus. We also observed a continuity between the drainage of the pancreatic head and the para-aortic region posteriorly. In view of the wealth of peri-pancreatic LNs, the number of LNs to harvest could be increased to improve nodal staging and prognostic evaluation. Pancreatic anatomy as described does not seem to be compatible with the sentinel LN procedure in pancreatic surgery. Finally, we are now able to offer an alternative to manual alignment with a semi-automated alignment.

Automated Image Alignment and Distortion Removal for 3-D Serial Sectioning with Electron Backscatter Diffraction

Automated Image Alignment and Distortion Removal for 3-D Serial Sectioning with Electron Backscatter Diffraction

Alternative automatic alignment method for specimen tilt-series images based on back-projected volume data cross-correlations.

We devised a new automatic image alignment method for a specimen tilt series; this method is based on the volume data cross-correlation among 3-D cross-sections reconstructed from different sets of projection images (including a single image) for tilt-series alignment or tilt-axis search purposes. This method requires neither markers nor image feature points traceable through the tilt series, and it was examined through simulations and applied to biological thin sections. The method automatically aligned tilt series centred at the correctly detected tilt axis with a precision sufficient for practical applications.

Study on Measuring System of Automatic Image Alignment Refractive Index Based on New Mathematical Model

With the development of measuring technology,the measuring accuracy of optical glass refractive index of the increasingly high demand,V prism refractometers is major general instrument for measuring the refractive index of optical glass,not only the simple device,convenient measurement,and this method has high precision performance,however,the accuracy is only attained ,which in the regulation of national metrology verification and the introduction of V prism refractometers in the literature,the classic formula calculation principle formula error caused by refractive index has more than .Based on the mechanical structure and optical transmission to improve the original V prism refractometers the refractive index of air,by considering the influence on measurement precision of V prism refractometer,to mathematical modeling of V prism refractometer the principle formula,V can be measured refractive prism refractometer rate accuracy increased to ,measurement repeatability less than ,has important practical significance for realizing high accuracy measurement of the refractive index of optical glass.

스테레오스코픽 3D 콘텐츠 제작의 효율성 향상을 위한 자동 영상정렬 및 모니터링 기법

고품질의 스테레오스코픽 3D 콘텐츠를 제작하기 위해서는 입체피로를 유발하는 문제요인들을 최소화하는 것이 중요하다. 촬영과정에서 스테레오 좌우 영상 간에 발생되는 수직시차는 입체피로의 주된 요인으로, 정확한 입체시를 유지하기 위해 필수적으로 제거될 필요가 있다. 본 논문에서는 콘텐츠 제작의 효율성 향상을 위하여 후처리 과정에서뿐만 아니라 촬영과 동시에 영상정렬이 수행된 결과를 모니터링할 수 있는 자동화된 방식의 영상처리 기법을 제안하였다. 제안방법은 대응점 추출과 기하구조 추정, 그리고 수직시차의 제거로 이어지는 편위수정 부분과 카메라 움직임 탐지 부분으로 구성되어 있으며, 각각에 대해 성능분석이 실시되었다. 실험결과, 제안방법은 비교분석을 위해 사용된 기존방법들에 비해 보다 향상된 성능을 나타냈으며, 카메라 움직임 탐지부분에서도 98.35% 성공률의 뛰어난 탐지성능을 보여주었다. 이러한 일련의 성능검증을 통해 실제 콘텐츠 제작현장에서 본 논문의 제안방법이 효과적으로 활용될 수 있음을 확인할 수 있었다. Minimization of visual fatigue is important for production of high quality stereoscopic 3D contents. Vertical disparity of stereo images occurred during contents production is considered as the main factor of visual fatigue. To ensure correct stereoscopy vertical disparity needs to be eliminated. In this paper, a method for automated image alignment was proposed for Stereoscopic 3D contents generation and post-processing steps. The proposed method consists of two parts: rectification for image alignment and camera motion detection. The proposed method showed that its rectification performance was the most superior among the existing methods tested and that camera motion detection had a success rate of 98.35%. Through these evaluations, we confirmed that the proposed method can be effectively applied to 3D contents production.

Epidermal keratinocyte polarity and motility require Ca2+ influx through TRPV1

Ca(2+) has long been known to play an important role in cellular polarity and guidance. We studied the role of Ca(2+) signaling during random and directed cell migration to better understand whether Ca(2+) directs cell motility from the leading edge and which ion channels are involved in this function by using primary zebrafish keratinocytes. Rapid line-scan and time-lapse imaging of intracellular Ca(2+) (Ca(2+)i) during migration and automated image alignment enabled us to characterize and map the spatiotemporal changes in Ca(2+)i. We show that asymmetric distributions of lamellipodial Ca(2+) sparks are encoded in frequency, not amplitude, and that they correlate with cellular rotation during migration. Directed migration during galvanotaxis increases the frequency of Ca(2+) sparks over the entire lamellipod; however, these events do not give rise to asymmetric Ca(2+)i signals that correlate with turning. We demonstrate that Ca(2+)-permeable channels within these cells are mechanically activated and include several transient receptor potential family members, including TRPV1. Last, we demonstrate that cell motility and Ca(2+)i activity are affected by pharmacological agents that target TRPV1, indicating a novel role for this channel during cell migration.

Automated, Feature-Based Image Alignment for High-Resolution Imaging Mass Spectrometry of Large Biological Samples

High-resolution imaging mass spectrometry of large biological samples is the goal of several research groups. In mosaic imaging, the most common method, the large sample is divided into a mosaic of small areas that are then analyzed with high resolution. Here we present an automated alignment routine that uses principal component analysis to reduce the uncorrelated noise in the imaging datasets, which previously obstructed automated image alignment. An additional signal quality metric ensures that only those regions with sufficient signal quality are considered. We demonstrate that this algorithm provides superior alignment performance than manual stitching and can be used to automatically align large imaging mass spectrometry datasets comprising many individual mosaic tiles.

Automated image alignment for 2D gel electrophoresis in a high-throughput proteomics pipeline

The quest for high-throughput proteomics has revealed a number of challenges in recent years. Whilst substantial improvements in automated protein separation with liquid chromatography and mass spectrometry (LC/MS), aka 'shotgun' proteomics, have been achieved, large-scale open initiatives such as the Human Proteome Organization (HUPO) Brain Proteome Project have shown that maximal proteome coverage is only possible when LC/MS is complemented by 2D gel electrophoresis (2-DE) studies. Moreover, both separation methods require automated alignment and differential analysis to relieve the bioinformatics bottleneck and so make high-throughput protein biomarker discovery a reality. The purpose of this article is to describe a fully automatic image alignment framework for the integration of 2-DE into a high-throughput differential expression proteomics pipeline. The proposed method is based on robust automated image normalization (RAIN) to circumvent the drawbacks of traditional approaches. These use symbolic representation at the very early stages of the analysis, which introduces persistent errors due to inaccuracies in modelling and alignment. In RAIN, a third-order volume-invariant B-spline model is incorporated into a multi-resolution schema to correct for geometric and expression inhomogeneity at multiple scales. The normalized images can then be compared directly in the image domain for quantitative differential analysis. Through evaluation against an existing state-of-the-art method on real and synthetically warped 2D gels, the proposed analysis framework demonstrates substantial improvements in matching accuracy and differential sensitivity. High-throughput analysis is established through an accelerated GPGPU (general purpose computation on graphics cards) implementation. Supplementary material, software and images used in the validation are available at http://www.proteomegrid.org/rain/.

Markov random field based automatic image alignment for electron tomography

We present a method for automatic full-precision alignment of the images in a tomographic tilt series. Full-precision automatic alignment of cryo electron microscopy images has remained a difficult challenge to date, due to the limited electron dose and low image contrast. These facts lead to poor signal to noise ratio (SNR) in the images, which causes automatic feature trackers to generate errors, even with high contrast gold particles as fiducial features. To enable fully automatic alignment for full-precision reconstructions, we frame the problem probabilistically as finding the most likely particle tracks given a set of noisy images, using contextual information to make the solution more robust to the noise in each image. To solve this maximum likelihood problem, we use Markov Random Fields (MRF) to establish the correspondence of features in alignment and robust optimization for projection model estimation. The resulting algorithm, called Robust Alignment and Projection Estimation for Tomographic Reconstruction, or RAPTOR, has not needed any manual intervention for the difficult datasets we have tried, and has provided sub-pixel alignment that is as good as the manual approach by an expert user. We are able to automatically map complete and partial marker trajectories and thus obtain highly accurate image alignment. Our method has been applied to challenging cryo electron tomographic datasets with low SNR from intact bacterial cells, as well as several plastic section and X-ray datasets.

Effect of Automated Image Registration on Radiologist Interpretation

In this study, we present preliminary data on the effect of automated 3D image alignment on the time to arrive at a decision about an imaging finding, the agreement of multiple of multiple observers, the prevalence of comparison examinations, and technical success rates for the image alignment algorithm. We found that automated image alignment reduced the average time to make a decision by 25% for cases where the structures are rigid, and when the scanning protocol is similar. For cases where these are not true, there is little or no benefit. In our practice, 54% of cases had prior examinations that could be automatically aligned. The overall benefit seen in our department for highly similar exams might be 20% for neuro and 10% for body; the benefit seen in other practices is likely to vary based on scanning practices and prevalence of prior examinations.

Fluorescent in situ sequencing on polymerase colonies

Integration of DNA isolation, amplification, and sequencing can be achieved by the use of polymerase colonies (polonies) and cycles of fluorescent dNTP incorporation. In this paper, we present four advances that bring us closer to sequencing genomes cost-effectively using the polony technology. First, a polymerase trapping technique enables efficient nucleotide extension by DNA polymerase in a polyacrylamide matrix and eliminates loss of enzyme during sequencing cycles. Next, we present two novel types of reversibly dye-labeled nucleotide analogues, show that DNA polymerase can incorporate these analogues, and demonstrate that the dyes can be removed by thiol reduction or light exposure. Using these nucleotides, we have sequenced multiple polonies in parallel. In addition, we have found that a high density of polonies can be achieved with minimal overlap between adjacent polonies by limiting the concentration of free primer in the polony amplification reactions. Finally, we have developed software for automated image alignment and sequence calling.

An automated image alignment system for the scanning electron microscope

AbstractWe have developed an automated image alignment system for the scanning electron microscope (SEM). This system enables specific locations on a sample to be located and automatically aligned with submicron accuracy. The system comprises a sample stage motorization and control unit together with dedicated imaging electronics and image processing software. The standard SEM sample stage is motorized in the X and Y axes with stepping motors which are fitted with rotary optical encoders. The imaging electronics are interfaced to beam deflection electronics of the SEM and provide the image data for the image processing software. The system initially moves the motorized sample stage to the area of interest and acquires an image. This image is compared with a reference image to determine the required adjustments to the stage position or beam deflection. This procedure is repeated until the area imaged by the SEM matches the reference image. A hierarchical image correlation technique is used to achieve submicron alignment accuracy in a few seconds. The ability to control the SEM beam deflection enables the images to be aligned with an accuracy far exceeding the positioning ability of the SEM stage. The alignment system may be used on a variety of samples without the need for registration or alignment marks since the features in the SEM image are used for alignment. This system has been used for the automatic inspection of devices on semiconductor wafers, and has also enabled the SEM to be used for direct write self‐aligned electron beam lithography.