Repeatability of \u3cem\u3eIn Vivo\u3c/em\u3e Parafoveal Cone Density and Spacing Measurements

Purpose. To assess the repeatability and measurement error associated with cone density and nearest neighbor distance (NND) estimates in images of the parafoveal cone mosaic obtained with an adaptive optics scanning light ophthalmoscope (AOSLO).Methods. Twenty-one participants with no known ocular pathology were recruited. Four retinal locations, approximately 0.65[degrees] eccentricity from the center of fixation, were imaged 10 times in randomized order with an AOSLO. Cone coordinates in each image were identified using an automated algorithm (with or without manual correction) from which cone density and NND were calculated. Owing to naturally occurring fixational instability, the 10 images recorded from a given location did not overlap entirely. We thus analyzed each image set both before and after alignment.Results. Automated estimates of cone density on the unaligned image sets showed a coefficient of repeatability of 11,769 cones/mm2 (17.1%). The primary reason for this variability appears to be fixational instability, as aligning the 10 images to include the exact same retinal area results in an improved repeatability of 4358 cones/mm2 (6.4%) using completely automated cone identification software. Repeatability improved further by manually identifying cones missed by the automated algorithm, with a coefficient of repeatability of 1967 cones/mm2 (2.7%). NND showed improved repeatability and was generally insensitive to the undersampling by the automated algorithm.Conclusions. As our data were collected in a young, healthy population, this likely represents a best-case estimate for corresponding measurements in patients with retinal disease. Similar studies need to be carried out on other imaging systems (including those using different imaging modalities, wavefront correction technology, and/or image analysis software), as repeatability would be expected to be highly sensitive to initial image quality and the performance of cone identification algorithms. Separate studies addressing intersession repeatability and interobserver reliability are also needed

Dynamic Analysis of Vascular Morphogenesis Using Transgenic Quail Embryos

Background: One of the least understood and most central questions confronting biologists is how initially simple clusters or sheet-like cell collectives can assemble into highly complex three-dimensional functional tissues and organs. Due to the limits of oxygen diffusion, blood vessels are an essential and ubiquitous presence in all amniote tissues and organs. Vasculogenesis, the de novo self-assembly of endothelial cell (EC) precursors into endothelial tubes, is the first step in blood vessel formation [1]. Static imaging and in vitro models are wholly inadequate to capture many aspects of vascular pattern formation in vivo, because vasculogenesis involves dynamic changes of the endothelial cells and of the forming blood vessels, in an embryo that is changing size and shape. Methodology/Principal Findings: We have generated Tie1 transgenic quail lines Tg(tie1:H2B-eYFP) that express H2B-eYFP in all of their endothelial cells which permit investigations into early embryonic vascular morphogenesis with unprecedented clarity and insight. By combining the power of molecular genetics with the elegance of dynamic imaging, we follow the precise patterning of endothelial cells in space and time. We show that during vasculogenesis within the vascular plexus, ECs move independently to form the rudiments of blood vessels, all while collectively moving with gastrulating tissues that flow toward the embryo midline. The aortae are a composite of somatic derived ECs forming its dorsal regions and the splanchnic derived ECs forming its ventral region. The ECs in the dorsal regions of the forming aortae exhibit variable mediolateral motions as they move rostrally; those in more ventral regions show significant lateral-to-medial movement as they course rostrally. Conclusions/Significance: The present results offer a powerful approach to the major challenge of studying the relative role(s) of the mechanical, molecular, and cellular mechanisms of vascular development. In past studies, the advantages of the molecular genetic tools available in mouse were counterbalanced by the limited experimental accessibility needed for imaging and perturbation studies. Avian embryos provide the needed accessibility, but few genetic resources. The creation of transgenic quail with labeled endothelia builds upon the important roles that avian embryos have played in previous studies of vascular development

Smart environment monitoring through micro unmanned aerial vehicles

In recent years, the improvements of small-scale Unmanned Aerial Vehicles (UAVs) in terms of flight time, automatic control, and remote transmission are promoting the development of a wide range of practical applications. In aerial video surveillance, the monitoring of broad areas still has many challenges due to the achievement of different tasks in real-time, including mosaicking, change detection, and object detection. In this thesis work, a small-scale UAV based vision system to maintain regular surveillance over target areas is proposed. The system works in two modes. The first mode allows to monitor an area of interest by performing several flights. During the first flight, it creates an incremental geo-referenced mosaic of an area of interest and classifies all the known elements (e.g., persons) found on the ground by an improved Faster R-CNN architecture previously trained. In subsequent reconnaissance flights, the system searches for any changes (e.g., disappearance of persons) that may occur in the mosaic by a histogram equalization and RGB-Local Binary Pattern (RGB-LBP) based algorithm. If present, the mosaic is updated. The second mode, allows to perform a real-time classification by using, again, our improved Faster R-CNN model, useful for time-critical operations. Thanks to different design features, the system works in real-time and performs mosaicking and change detection tasks at low-altitude, thus allowing the classification even of small objects. The proposed system was tested by using the whole set of challenging video sequences contained in the UAV Mosaicking and Change Detection (UMCD) dataset and other public datasets. The evaluation of the system by well-known performance metrics has shown remarkable results in terms of mosaic creation and updating, as well as in terms of change detection and object detection

A review and open issues of multifarious image steganography techniques in spatial domain

Nowadays, information hiding is becoming a helpful technique and fetch more attention due fast growth of using internet, it is applied for sending secret information by using different techniques. Steganography is one of major important technique in information hiding. Steganography is science of concealing the secure information within a carrier object to provide the secure communication though the internet, so that no one can recognize and detect it’s except the sender & receiver. In steganography, many various carrier formats can be used such as an image, video, protocol, audio. The digital image is most popular used as a carrier file due its frequency on internet. There are many techniques variable for image steganography, each has own strong and weak points. In this study, we conducted a review of image steganography in spatial domain to explore the term image steganography by reviewing, collecting, synthesizing and analyze the challenges of different studies which related to this area published from 2014 to 2017. The aims of this review is provides an overview of image steganography and comparison between approved studies are discussed according to the pixel selection, payload capacity and embedding algorithm to open important research issues in the future works and obtain a robust method

Application of unmanned aerial systems for high throughput phenotyping of large wheat breeding nurseries

Citation: Haghighattalab, A., Perez, L. G., Mondal, S., Singh, D., Schinstock, D., Rutkoski, J., . . . Poland, J. (2016). Application of unmanned aerial systems for high throughput phenotyping of large wheat breeding nurseries. Plant Methods, 12, 15. https://doi.org/10.1186/s13007-016-0134-6Background: Low cost unmanned aerial systems (UAS) have great potential for rapid proximal measurements of plants in agriculture. In the context of plant breeding and genetics, current approaches for phenotyping a large number of breeding lines under field conditions require substantial investments in time, cost, and labor. For field-based high-throughput phenotyping (HTP), UAS platforms can provide high-resolution measurements for small plot research, while enabling the rapid assessment of tens-of-thousands of field plots. The objective of this study was to complete a baseline assessment of the utility of UAS in assessment field trials as commonly implemented in wheat breeding programs. We developed a semi-automated image-processing pipeline to extract plot level data from UAS imagery. The image dataset was processed using a photogrammetric pipeline based on image orientation and radiometric calibration to produce orthomosaic images. We also examined the relationships between vegetation indices (VIs) extracted from high spatial resolution multispectral imagery collected with two different UAS systems (eBee Ag carrying MultiSpec 4C camera, and IRIS+ quadcopter carrying modified NIR Canon S100) and ground truth spectral data from hand-held spectroradiometer. Results: We found good correlation between the VIs obtained from UAS platforms and ground-truth measurements and observed high broad-sense heritability for VIs. We determined radiometric calibration methods developed for satellite imagery significantly improved the precision of VIs from the UAS. We observed VIs extracted from calibrated images of Canon S100 had a significantly higher correlation to the spectroradiometer (r = 0.76) than VIs from the MultiSpec 4C camera (r = 0.64). Their correlation to spectroradiometer readings was as high as or higher than repeated measurements with the spectroradiometer per se. Conclusion: The approaches described here for UAS imaging and extraction of proximal sensing data enable collection of HTP measurements on the scale and with the precision needed for powerful selection tools in plant breeding. Low-cost UAS platforms have great potential for use as a selection tool in plant breeding programs. In the scope of tools development, the pipeline developed in this study can be effectively employed for other UAS and also other crops planted in breeding nurseries

Close-range photogrammetry for accurate deformation distribution measurement

© 2017 Taylor & Francis Group, London. This paper introduces a methodology for improving the accuracy of Deformation Distribution Measurement (DDM) using close-range photogrammetry. After reviewing various algorithms for 2D Digital Image Correlation (DIC), Zero-Normalized Cross-Correlation (ZNCC) is selected for deformation measurement. The impact of several other factors on DIC measurement accuracy has been investigated, including the type of imaging sensors, the contrast and pattern of a specimen, and searching window size. Optimal option of these factors is proposed. The technique is utilized in the experiment of applying static loading on a replica of a concrete structural component used for Sydney Harbour Bridge. Test results presented in the paper include DIC measurements and validation data from conventional sensors

Quantification of virus syndrome in chili peppers

One of the most important problems to produce chili crops is the presence of diseases caused by pathogen agents, such as viruses, therefore, there is a substantial necessity to better predict the behavior of the diseases of these crops, determining a more precise quantification of the disease’s syndrome that allows the investigators to evaluate better practices, from handling to the experimental level and will permit producers to take opportunistic corrective action thereby, reducing production loses and increasing the quality of the crop. This review discussed methods that have been used for the quantification of disease in plants, specifically for chili peppers crops, thereby, suggesting a better alternative for the quantification of the disease’ syndromes in regards to this crop. The result of these reflections indicates that most methods used for quantification are based on visual assessments, discarding differences of data between distinctive evaluators. These methods generate subjective results.Key words: Quantification, plant diseases, severity, syndrome, viruses