Repeatability of measuring corneal subbasal nerve fiber length in individuals with Type 2 Diabetes

Purpose: To analyze the repeatability of measuring nerve fiber length (NFL) from images of the human corneal subbasal nerve plexus using semiautomated software. Methods: Images were captured from the corneas of 50 subjects with type 2 diabetes mellitus who showed varying severity of neuropathy, using the Heidelberg Retina Tomograph 3 with Rostock Corneal Module. Semiautomated nerve analysis software was independently used by two observers to determine NFL from images of the subbasal nerve plexus. This procedure was undertaken on two occasions, 3 days apart. Results: The intraclass correlation coefficient values were 0.95 (95% confidence intervals: 0.92–0.97) for individual subjects and 0.95 (95% confidence intervals: 0.74–1.00) for observer. Bland-Altman plots of the NFL values indicated a reduced spread of data with lower NFL values. The overall spread of data was less for (a) the observer who was more experienced at analyzing nerve fiber images and (b) the second measurement occasion. Conclusions: Semiautomated measurement of NFL in the subbasal nerve fiber layer is highly repeatable. Repeatability can be enhanced by using more experienced observers. It may be possible to markedly improve repeatability when measuring this anatomic structure using fully automated image analysis software.

Diagnosing dry eye with dynamic-area high-speed videokeratoscopy

Dry eye syndrome is one of the most commonly reported eye health conditions. Dynamic-area highspeed videokeratoscopy (DA-HSV) represents a promising alternative to the most invasive clinical methods for the assessment of the tear film surface quality (TFSQ), particularly as Placido-disk videokeratoscopy is both relatively inexpensive and widely used for corneal topography assessment. Hence, improving this technique to diagnose dry eye is of clinical significance and the aim of this work. First, a novel ray-tracing model is proposed that simulates the formation of a Placido image. This model shows the relationship between tear film topography changes and the obtained Placido image and serves as a benchmark for the assessment of indicators of the ring’s regularity. Further, a novel block-feature TFSQ indicator is proposed for detecting dry eye from a series of DA-HSV measurements. The results of the new indicator evaluated on data from a retrospective clinical study, which contains 22 normal and 12 dry eyes, have shown a substantial improvement of the proposed technique to discriminate dry eye from normal tear film subjects. The best discrimination was obtained under suppressed blinking conditions. In conclusion,this work highlights the potential of the DA-HSV as a clinical tool to diagnose dry eye syndrome.

Machine recognition of hand-drawn circuit diagrams

An application of image processing techniques to recognition of hand-drawn circuit diagrams is presented. The scanned image of a diagram is pre-processed to remove noise and converted to bilevel. Morphological operations are applied to obtain a clean, connected representation using thinned lines. The diagram comprises of nodes, connections and components. Nodes and components are segmented using appropriate thresholds on a spatially varying object pixel density. Connection paths are traced using a pixel-stack. Nodes are classified using syntactic analysis. Components are classified using a combination of invariant moments, scalar pixel-distribution features, and vector relationships between straight lines in polygonal representations. A node recognition accuracy of 82% and a component recognition accuracy of 86% was achieved on a database comprising 107 nodes and 449 components. This recogniser can be used for layout “beautification” or to generate input code for circuit analysis and simulation packages

Variational Bayes and the reduced dependence approximation for the autologistic model on an irregular grid with applications

Discrete Markov random field models provide a natural framework for representing images or spatial datasets. They model the spatial association present while providing a convenient Markovian dependency structure and strong edge-preservation properties. However, parameter estimation for discrete Markov random field models is difficult due to the complex form of the associated normalizing constant for the likelihood function. For large lattices, the reduced dependence approximation to the normalizing constant is based on the concept of performing computationally efficient and feasible forward recursions on smaller sublattices which are then suitably combined to estimate the constant for the whole lattice. We present an efficient computational extension of the forward recursion approach for the autologistic model to lattices that have an irregularly shaped boundary and which may contain regions with no data; these lattices are typical in applications. Consequently, we also extend the reduced dependence approximation to these scenarios enabling us to implement a practical and efficient non-simulation based approach for spatial data analysis within the variational Bayesian framework. The methodology is illustrated through application to simulated data and example images. The supplemental materials include our C++ source code for computing the approximate normalizing constant and simulation studies.

An integrated approach for precise road reconstruction from aerial imagery and LiDAR data

Accurate and detailed road models play an important role in a number of geospatial applications, such as infrastructure planning, traffic monitoring, and driver assistance systems. In this thesis, an integrated approach for the automatic extraction of precise road features from high resolution aerial images and LiDAR point clouds is presented. A framework of road information modeling has been proposed, for rural and urban scenarios respectively, and an integrated system has been developed to deal with road feature extraction using image and LiDAR analysis. For road extraction in rural regions, a hierarchical image analysis is first performed to maximize the exploitation of road characteristics in different resolutions. The rough locations and directions of roads are provided by the road centerlines detected in low resolution images, both of which can be further employed to facilitate the road information generation in high resolution images. The histogram thresholding method is then chosen to classify road details in high resolution images, where color space transformation is used for data preparation. After the road surface detection, anisotropic Gaussian and Gabor filters are employed to enhance road pavement markings while constraining other ground objects, such as vegetation and houses. Afterwards, pavement markings are obtained from the filtered image using the Otsu's clustering method. The final road model is generated by superimposing the lane markings on the road surfaces, where the digital terrain model (DTM) produced by LiDAR data can also be combined to obtain the 3D road model. As the extraction of roads in urban areas is greatly affected by buildings, shadows, vehicles, and parking lots, we combine high resolution aerial images and dense LiDAR data to fully exploit the precise spectral and horizontal spatial resolution of aerial images and the accurate vertical information provided by airborne LiDAR. Objectoriented image analysis methods are employed to process the feature classiffcation and road detection in aerial images. In this process, we first utilize an adaptive mean shift (MS) segmentation algorithm to segment the original images into meaningful object-oriented clusters. Then the support vector machine (SVM) algorithm is further applied on the MS segmented image to extract road objects. Road surface detected in LiDAR intensity images is taken as a mask to remove the effects of shadows and trees. In addition, normalized DSM (nDSM) obtained from LiDAR is employed to filter out other above-ground objects, such as buildings and vehicles. The proposed road extraction approaches are tested using rural and urban datasets respectively. The rural road extraction method is performed using pan-sharpened aerial images of the Bruce Highway, Gympie, Queensland. The road extraction algorithm for urban regions is tested using the datasets of Bundaberg, which combine aerial imagery and LiDAR data. Quantitative evaluation of the extracted road information for both datasets has been carried out. The experiments and the evaluation results using Gympie datasets show that more than 96% of the road surfaces and over 90% of the lane markings are accurately reconstructed, and the false alarm rates for road surfaces and lane markings are below 3% and 2% respectively. For the urban test sites of Bundaberg, more than 93% of the road surface is correctly reconstructed, and the mis-detection rate is below 10%.

Investigating the change in three dimensional deformity for idiopathic scoliosis using axially loaded MRI

Background: Adolescent idiopathic scoliosis is a complex three-dimensional deformity, involving a lateral deformity in the coronal plane and axial rotation of the vertebrae in the transverse plane. Gravitational loading plays an important biomechanical role in governing the coronal deformity, however, less is known about how they influence the axial deformity. This study investigates the change in three-dimensional deformity of a series of scoliosis patients due to compressive axial loading. Methods: Magnetic resonance imaging scans were obtained and coronal deformity (measured using the coronal Cobb angle) and axial rotations measured for a group of 18 scoliosis patients (Mean major Cobb angle was 43.4 o). Each patient was scanned in an unloaded and loaded condition while compressive loads equivalent to 50% body mass were applied using a custom developed compressive device. Findings: The mean increase in major Cobb angle due to compressive loading was 7.4 o (SD 3.5 o). The most axially rotated vertebra was observed at the apex of the structural curve and the largest average intravertebral rotations were observed toward the limits of the coronal deformity. A level-wise comparison showed no significant difference between the average loaded and unloaded vertebral axial rotations (intra-observer error = 2.56 o) or intravertebral rotations at each spinal level. Interpretation: This study suggests that the biomechanical effects of axial loading primarily influence the coronal deformity, with no significant change in vertebral axial rotation or intravertebral rotation observed between the unloaded and loaded condition. However, the magnitude of changes in vertebral rotation with compressive loading may have been too small to detect given the resolution of the current technique.

Studies of bone cell adhesion and proliferation on ion implanted titanium discs

Argon ions were implanted on titanium discs to study its effect on bone cell adhesion and proli feration. Polished titanium discs were prepared and implanted with argon ions with different doses. Afterwards the samples were sterilized using UV light, inocu lated with human bone cells and incubated. Once fixed and rinsed, image analysis has been used to quantify the number of cells attached to the titanium discs. Cell proliferation tests were also conducted after a period of 120 hours. Cell adhesion was seen to be higher with ion im planted surface. SEM analysis has shown that the cells attached spread more on ion implanted surface. The numbers of cells attached were seen to be higher on implanted surfaces; they tend to occupy wider areas with healthier cells.

Fast and robust stereo matching algorithms for mining automation

The mining environment, being complex, irregular and time varying, presents a challenging prospect for stereo vision. The objective is to produce a stereo vision sensor suited to close-range scenes consisting primarily of rocks. This sensor should be able to produce a dense depth map within real-time constraints. Speed and robustness are of foremost importance for this investigation. A number of area based matching metrics have been implemented, including the SAD, SSD, NCC, and their zero-meaned versions. The NCC and the zero meaned SAD and SSD were found to produce the disparity maps with the highest proportion of valid matches. The plain SAD and SSD were the least computationally expensive, due to all their operations taking place in integer arithmetic, however, they were extremely sensitive to radiometric distortion. Non-parametric techniques for matching, in particular, the rank and the census transform, have also been investigated. The rank and census transforms were found to be robust with respect to radiometric distortion, as well as being able to produce disparity maps with a high proportion of valid matches. An additional advantage of both the rank and the census transform is their amenability to fast hardware implementation.

Porosity of serially sectioned interplanetary dust particles

The application of epoxy embedding and microtomy to individual chondritic interplanetary dust particles (lOP's)(Bradley and Brownlee, 1986a) provides not only higher precision in thin-film elemental analyses (Bradley and Brownlee, 19861:1), but also allows a wealth of other important techniques for the micro-characterization of these primitive extraterrestrial materials. For example, individual sections (e.g. 100 nm thick) or a series of sections, can be examined using image analysis techniques which utilize either transmitted or scanned secondary electron images, or alternatively, secondary X-ray spectra collected concurrently from a given region of sample. Individual particles, or groups of particles with similar image characteristics can then be rapidly identified using conventional grey-scale/particle recognition techniques for each microtomed section of lOP. This type of image analysis provides a suitable method for determination of particle size and shape distribution as well as porosity throughout the aggregate.

Kaolinite particle sizes in the <2 µM range using laser scattering

The Clay Minerals Society Source Clay kaolinites, Georgia KGa-1 and KGa-2, have been subjected to particle size determinations by 1) conventional sedimentation methods, 2) electron microscopy and image analysis, and 3) laser scattering using improved algorithms for the interaction of light with small particles. Particle shape, size distribution, and crystallinity vary considerably for each kaolinite. Replicate analyses of separated size fractions showed that in the <2 µm range, the sedimentation/centrifugation method of Tanner and Jackson (1947) is reproducible for different kaolinite types and that the calculated size ranges are in reasonable agreement with the size bins estimated from laser scattering. Particle sizes determined by laser scattering must be calculated using Mie theory when the dominant particle size is less than ∼5 µm. Based on this study of two well-known and structurally different kaolinites, laser scattering, with improved data reduction algorithms that include Mie theory, should be considered an internally consistent and rapid technique for clay particle sizing.

Experimental investigation of wheel/rail rolling contact at railhead edge

Wheel-rail rolling contact at railhead edge, such as a gap in an insulated rail joint, is a complex problem; there are only limited analytical, numerical and experimental studies available on this problem in the academic literature. This paper describes experimental and numerical investigations of railhead strains in the vicinity of the edge under the contact of a loaded wheel. A full-scale test rig was developed to cyclically apply wheel/rail rolling contact load to the edge zone of the railhead. An image analysis technique was employed to determine the railhead vertical, lateral and shear strain components. The vertical strains determined using the image analysis method have been validated with the strain gauge measurements and used for the calibration of a 3D nonlinear Finite Element Model (FEM) that simulates the wheel/rail contact at the railhead edge and use suitable boundary conditions commensurate to the experimental setup. The FEM was then used to determine other states of strains.

Morphology-based model for predicting osteocyte-like cell line (MLO-Y4) growth process

This work has led to the development of empirical mathematical models to quantitatively predicate the changes of morphology in osteocyte-like cell lines (MLO-Y4) in culture. MLO-Y4 cells were cultured at low density and the changes in morphology recorded over 11 hours. Cell area and three dimensional shape features including aspect ratio, circularity and solidity were then determined using widely accepted image analysis software (ImageJTM). Based on the data obtained from the imaging analysis, mathematical models were developed using the non-linear regression method. The developed mathematical models accurately predict the morphology of MLO-Y4 cells for different culture times and can, therefore, be used as a reference model for analyzing MLO-Y4 cell morphology changes within various biological/mechanical studies, as necessary.

Experimental investigation of the governing parameters in the electrospinning of poly(3-hydroxybutyrate) scaffolds : structural characteristics of the pores

We sought to determine the impact of electrospinning parameters on a trustworthy criterion that could evidently improve the maximum applicability of fibrous scaffolds for tissue regeneration. We used an image analysis technique to elucidate the web permeability index (WPI) by modeling the formation of electrospun scaffolds. Poly(3-hydroxybutyrate) (P3HB) scaffolds were fabricated according to predetermined conditions of levels in a Taguchi orthogonal design. The material parameters were the polymer concentration, conductivity, and volatility of the solution. The processing parameters were the applied voltage and nozzle-to-collector distance. With a law to monitor the WPI values when the polymer concentration or the applied voltage was increased, the pore interconnectivity was decreased. The quality of the jet instability altered the pore numbers, areas, and other structural characteristics, all of which determined the scaffold porosity and aperture interconnectivity. An initial drastic increase was observed in the WPI values because of the chain entanglement phenomenon above a 6 wt % P3HB content. Although the solution mixture significantly (p < 0.05) changed the scaffold architectural characteristics as a function of the solution viscosity and surface tension, it had a minor impact on the WPI values. The solution mixture gained the third place of significance, and the distance was approved as the least important factor.

Sensitivity of edge detection methods for quantifying cell migration assays

Quantitative imaging methods to analyze cell migration assays are not standardized. Here we present a suite of two–dimensional barrier assays describing the collective spreading of an initially–confined population of 3T3 fibroblast cells. To quantify the motility rate we apply two different automatic image detection methods to locate the position of the leading edge of the spreading population after 24, 48 and 72 hours. These results are compared with a manual edge detection method where we systematically vary the detection threshold. Our results indicate that the observed spreading rates are very sensitive to the choice of image analysis tools and we show that a standard measure of cell migration can vary by as much as 25% for the same experimental images depending on the details of the image analysis tools. Our results imply that it is very difficult, if not impossible, to meaningfully compare previously published measures of cell migration since previous results have been obtained using different image analysis techniques and the details of these techniques are not always reported. Using a mathematical model, we provide a physical interpretation of our edge detection results. The physical interpretation is important since edge detection algorithms alone do not specify any physical measure, or physical definition, of the leading edge of the spreading population. Our modeling indicates that variations in the image threshold parameter correspond to a consistent variation in the local cell density. This means that varying the threshold parameter is equivalent to varying the location of the leading edge in the range of approximately 1–5% of the maximum cell density.

Quantifying spatial structure in experimental observations and agent-based simulations using pair-correlation functions

We define a pair-correlation function that can be used to characterize spatiotemporal patterning in experimental images and snapshots from discrete simulations. Unlike previous pair-correlation functions, the pair-correlation functions developed here depend on the location and size of objects. The pair-correlation function can be used to indicate complete spatial randomness, aggregation or segregation over a range of length scales, and quantifies spatial structures such as the shape, size and distribution of clusters. Comparing pair-correlation data for various experimental and simulation images illustrates their potential use as a summary statistic for calibrating discrete models of various physical processes.