Fusion of morphological images for airborne target detection

Several track-before-detection approaches for image based aircraft detection have recently been examined in an important automated aircraft collision detection application. A particularly popular approach is a two stage processing paradigm which involves: a morphological spatial filter stage (which aims to emphasize the visual characteristics of targets) followed by a temporal or track filter stage (which aims to emphasize the temporal characteristics of targets). In this paper, we proposed new spot detection techniques for this two stage processing paradigm that fuse together raw and morphological images or fuse together various different morphological images (we call these approaches morphological reinforcement). On the basis of flight test data, the proposed morphological reinforcement operations are shown to offer superior signal to-noise characteristics when compared to standard spatial filter options (such as the close-minus-open and adaptive contour morphological operations). However, system operation characterised curves, which examine detection verses false alarm characteristics after both processing stages, illustrate that system performance is very data dependent.

Corneal nerve structure and function as markers of diabetic neuropathy

Diabetic neuropathy is a significant clinical problem that currently has no effective therapy, and in advanced cases, leads to foot ulceration and lower limb amputation. The accurate detection, characterisation and quantification of this condition are important in order to define at-risk patients, anticipate deterioration, monitor progression and assess new therapies. This thesis evaluates novel corneal methods of assessing diabetic neuropathy. Over the past several years two new non-invasive corneal markers have emerged, and in cross-sectional studies have demonstrated their ability to stratify the severity of this disease. Corneal confocal microscopy (CCM) allows quantification of corneal nerve parameters and non-contact corneal aesthesiometry (NCCA), the presumed functional correlate of corneal structure, assesses the sensitivity of the cornea. Both these techniques are quick to perform, produce little or no discomfort for the patient, and with automatic analysis paradigms developed, are suitable for clinical settings. Each has advantages and disadvantages over established techniques for assessing diabetic neuropathy. New information is presented regarding measurement bias of CCM images, and a unique sampling paradigm and associated accuracy determination method of combinations is described. A novel high-speed corneal nerve mapping procedure has been developed and application of this procedure in individuals with neuropathy has revealed regions of sub-basal nerve plexus that dictate further evaluation, as they appear to show earlier signs of damage than the central region of the cornea that has to date been examined. The discriminative capacity of corneal sensitivity measured by NCCA is revealed to have reasonable potential as a marker of diabetic neuropathy. Application of these new corneal markers for longitudinal evaluation of diabetic neuropathy has the potential to reduce dependence on more invasive, costly, and time-consuming assessments, such as skin biopsy.

Physically sound vehicle-driver model for realistic microscopic simulation

In microscopic traffic simulators, the interaction between vehicles is considered. The dynamics of the system then becomes an emergent property of the interaction between its components. Such interactions include lane-changing, car-following behaviours and intersection management. Although, in some cases, such simulators produce realistic prediction, they do not allow for an important aspect of the dynamics, that is, the driver-vehicle interaction. This paper introduces a physically sound vehicle-driver model for realistic microscopic simulation. By building a nanoscopic traffic simulation model that uses steering angle and throttle position as parameters, the model aims to overcome unrealistic acceleration and deceleration values, as found in various microscopic simulation tools. A physics engine calculates the driving force of the vehicle, and the preliminary results presented here, show that, through a realistic driver-vehicle-environment simulator, it becomes possible to model realistic driver and vehicle behaviours in a traffic simulation.

Reading images : the book club in the art gallery

This paper seeks to document and understand one instance of community-university engagement: that of an on-going book club organised in conjunction with public art exhibitions. The curator of the Queensland University of Technology (QUT) Art Museum invited the authors, three postgraduate research students in the faculty of Creative Writing and Literary Studies at QUT, to facilitate an informal book club. The purpose of the book club was to generate discussion, through engagement with fiction, around the themes and ideas explored in the Art Museum’s exhibitions. For example, during the William Robinson exhibition, which presented evocative images of the environment around Brisbane, Queensland, the book club explored texts that symbolically represented aspects of the Australian landscape in a variety of modes and guises. This paper emerges as a result of the authors’ observations during, and reflections on, their experiences facilitating the book club. It responds to the research question, how can we create a best practice model to engage readers through open-ended, reciprocal discussion of fiction, while at the same time encouraging interactions in the gallery space? To provide an overview of reading practices in book clubs, we rely on Jenny Hartley’s seminal text on the subject, The Reading Groups Book (2002). Although the book club was open to all members of the community, the participants were generally women. Elizabeth Long, in Book Clubs: Woman and the Uses of Reading in the Everyday (2003), offers a comprehensive account of women’s interactions as they engage in a reading community. Long (2003, 2) observes that an image of the solitary reader governs our understanding of reading. Long challenges this notion, arguing that reading is profoundly social (ibid), and, as women read and talk in book clubs, ‘they are supporting each other in a collective working-out of their relationship to a particular historical movement and the particular social conditions that characterise it’ (Long 2003, 22). Despite the book club’s capacity to act as a forum for analytical discussion, DeNel Rehberg Sedo (2010, 2) argues that there are barriers to interaction in such a space, including that members require a level of cultural capital and literacy before they feel comfortable to participate. How then can we seek to make book clubs more inclusive, and encourage readers to discuss and question outside of their comfort zone? How can we support interactions with texts and images? In this paper, we draw on pragmatic and self-reflective practice methods to document and evaluate the development of the book club model designed to facilitate engagement. We discuss how we selected texts, negotiating the dual needs of relevance to the exhibition and engagement with, and appeal to, the community. We reflect on developing questions and material prior to the book club to encourage interaction, and describe how we developed a flexible approach to question-asking and facilitating discussion. We conclude by reflecting on the outcomes of and improvements to the model.

Real-time power line extraction from unmanned aerial system video images

In this paper a real-time vision based power line extraction solution is investigated for active UAV guidance. The line extraction algorithm starts from ridge points detected by steerable filters. A collinear line segments fitting algorithm is followed up by considering global and local information together with multiple collinear measurements. GPU boosted algorithm implementation is also investigated in the experiment. The experimental result shows that the proposed algorithm outperforms two baseline line detection algorithms and is able to fitting long collinear line segments. The low computational cost of the algorithm make suitable for real-time applications.

Integration of medical images to the teaching of systematic pathology : an evaluation of relevance

A sound knowledge of pathological disease processes is required for professional practice within health professions. The project described in this paper reviewed the resources currently available for the delivery of systematic pathology tutorials. Additional complementary resources were developed and the inclusion of these additional learning resources in practical tutorial sessions was evaluated for their impact on student learning. Student evaluation of the learning resources was undertaken across one semester with two different cohorts of health profession students using questionnaires and focus group discussion. Both cohorts reported an enhancement to their understanding of pathological disease processes through the use of the additional resources. Results indicate student perception of the value of the resources correlates with staff perception and is independent of prior experiences.

Microscopic traffic hysteresis in traffic oscillations : a behavioral perspective

This paper studies traffic hysteresis arising in traffic oscillations from a behavioral perspective. It is found that the occurrence and type of traffic hysteresis is closely correlated with driver behavior when experiencing traffic oscillations and with the time driver reaction begins relative to the starting deceleration wave. Statistical results suggest that driver behavior is different depending on its position along the oscillation. This suggests that different car-following models should be used inside the different stages of an oscillation in order to replicate realistic congestion features.

Utility of corneal confocal microscopy for assessing mild diabetic neuropathy: baseline findings of the LANDMark study

Background:  For those in the field of managing diabetic complications, the accurate diagnosis and monitoring of diabetic peripheral neuropathy (DPN) continues to be a challenge. Assessment of sub-basal corneal nerve morphology has recently shown promise as a novel ophthalmic marker for the detection of DPN. Methods:  Two hundred and thirty-one individuals with diabetes with predominantly mild or no neuropathy and 61 controls underwent evaluation of diabetic neuropathy symptom score, neuropathy disability score, testing with 10 g monofilament, quantitative sensory testing (warm, cold, vibration detection) and nerve conduction studies. Corneal nerve fibre length, branch density and tortuosity were measured using corneal confocal microscopy. Differences in corneal nerve morphology between individuals with and without DPN and controls were investigated using analysis of variance and correlations were determined between corneal morphology and established tests of, and risk factors for, DPN. Results:  Corneal nerve fibre length was significantly reduced in diabetic individuals with mild DPN compared with both controls (p < 0.001) and diabetic individuals without DPN (p = 0.012). Corneal nerve branch density was significantly reduced in individuals with mild DPN compared with controls (p = 0.032). Corneal nerve fibre tortuosity did not show significant differences. Corneal nerve fibre length and corneal nerve branch density showed modest correlations to most measures of neuropathy, with the strongest correlations to nerve conduction study parameters (r = 0.15 to 0.25). Corneal nerve fibre tortuosity showed only a weak correlation to the vibration detection threshold. Corneal nerve fibre length was inversely correlated to glycated haemoglobin (r = -0.24) and duration of diabetes (r = -0.20). Conclusion:  Assessment of corneal nerve morphology is a non-invasive, rapid test capable of showing differences between individuals with and without DPN. Corneal nerve fibre length shows the strongest associations with other diagnostic tests of neuropathy and with established risk factors for neuropathy.

Comparison and modification of car following models toward a more accurate microscopic simulation parameters reproduction

Traffic safety studies demand more than what current micro-simulation models can provide as they presume that all drivers of motor vehicles exhibit safe behaviours. Several car-following models are used in various micro-simulation models. This research compares the mainstream car following models’ capabilities of emulating precise driver behaviour parameters such as headways and Time to Collisions. The comparison firstly illustrates which model is more robust in the metric reproduction. Secondly, the study conducted a series of sensitivity tests to further explore the behaviour of each model. Based on the outcome of these two steps exploration of the models, a modified structure and parameters adjustment for each car-following model is proposed to simulate more realistic vehicle movements, particularly headways and Time to Collision, below a certain critical threshold. NGSIM vehicle trajectory data is used to evaluate the modified models performance to assess critical safety events within traffic flow. The simulation tests outcomes indicate that the proposed modified models produce better frequency of critical Time to Collision than the generic models, while the improvement on the headway is not significant. The outcome of this paper facilitates traffic safety assessment using microscopic simulation.

The rationale for using microscopic units of a donor matrix in cartilage defect repair

The efficacy of existing articular cartilage defect repair strategies are limited. Native cartilage tissue forms via a series of exquisitely orchestrated morphogenic events spanning through gestation into early childhood. However, defect repair must be achieved in a non-ideal microenvironment over an accelerated time-frame compatible with the normal life of an adult patient. Scaffolds formed from decellularized tissues are commonly utilized to enable the rapid and accurate repair of tissues such as skin, bladder and heart valves. The intact extracellular matrix remaining following the decellularization of these relatively low-matrix-density tissues is able to rapidly and accurately guide host cell repopulation. By contrast, the extraordinary density of cartilage matrix limits both the initial decellularization of donor material as well as its subsequent repopulation. Repopulation of donor cartilage matrix is generally limited to the periphery, with repopulation of lacunae deeper within the matrix mass being highly inefficient. Herein, we review the relevant literature and discuss the trend toward the use of decellularized donor cartilage matrix of microscopic dimensions. We show that 2-µm microparticles of donor matrix are rapidly integrate with articular chondrocytes, forming a robust cartilage-like composites with enhanced chondrogenic gene expression. Strategies for the clinical application of donor matrix microparticles in cartilage defect repair are discussed.

Microscopic cooperative traffic based on NGSIM data

The deployment of new emerging technologies, such as cooperative systems, allows the traffic community to foresee relevant improvements in terms of traffic safety and efficiency. Vehicles are able to communicate on the local traffic state in real time, which could result in an automatic and therefore better reaction to the mechanism of traffic jam formation. An upstream single hop radio broadcast network can improve the perception of each cooperative driver within radio range and hence the traffic stability. The impact of a cooperative law on traffic congestion appearance is investigated, analytically and through simulation. Ngsim field data is used to calibrate the Optimal Velocity with Relative Velocity (OVRV) car following model and the MOBIL lane-changing model is implemented. Assuming that congestion can be triggered either by a perturbation in the instability domain or by a critical lane changing behavior, the calibrated car following behavior is used to assess the impact of a microscopic cooperative law on abnormal lane changing behavior. The cooperative law helps reduce and delay traffic congestion as it increases traffic flow stability.

Why we need a population-based approach to clinical indicators for cancer: a case study using microscopic confirmation of lung cancer in Queensland

An important function of clinical cancer registries is to provide feedback to clinicians on various performance measures. To date, most clinical cancer registries in Australia are located in tertiary academic hospitals, where adherence to guidelines is probably already high. Microscopic confirmation is an important process measure for lung cancer care. We found that the proportion of patients with lung cancer without microscopic confirmation was much higher in regional public hospitals (27.1%) than in tertiary hospitals (7.5%), and this disparity remained after adjusting for age, sex and comorbidities. The percentage was also higher in the private than in the public sector. This case study shows that we need a population-based approach to measuring clinical indicators that includes regional public hospitals as a matter of priority and should ideally include the private sector.

A comparison of calculated and experimental HRTEM images of twinned boron carbide

High resolution TEM images of boron carbide (B13C2) have been recorded and compared with images calculated using the multislice method as implemented by M. A. O'Keefe in the SHRLI programs. Images calculated for the [010] zone, using machine parameters for the JEOL 2000FX AEM operating at 200 keV, indicate that for the structure model of Will et al., the optimum defocus image can be interpreted such that white spots correspond to B12 icosahedra for thin specimens and to low density channels through the structure adjacent to the direct inter-icosahedral bonds for specimens of intermediate thickness (-40 > t > -100 nm). With this information, and from the symmetry observed in the TEM images, it is likely that the (101) twin plane passes through the center of icosahedron located at the origin. This model was tested using the method of periodic continuation. Resulting images compare favorably with experimental images, thus supporting the structural model. The introduction of a (101) twin plane through the origin creates distortions to the icosahedral linkages as well as to the intra-icosahedral bonding. This increases the inequivalence of adjacent icosahedral sites along the twin plane, and thereby increases the likelihood of bipolaron hopping.

Breast cancer detection from thermal images using bispectral invariant features

Highly sensitive infrared (IR) cameras provide high-resolution diagnostic images of the temperature and vascular changes of breasts. These images can be processed to emphasize hot spots that exhibit early and subtle changes owing to pathology. The resulting images show clusters that appear random in shape and spatial distribution but carry class dependent information in shape and texture. Automated pattern recognition techniques are challenged because of changes in location, size and orientation of these clusters. Higher order spectral invariant features provide robustness to such transformations and are suited for texture and shape dependent information extraction from noisy images. In this work, the effectiveness of bispectral invariant features in diagnostic classification of breast thermal images into malignant, benign and normal classes is evaluated and a phase-only variant of these features is proposed. High resolution IR images of breasts, captured with measuring accuracy of ±0.4% (full scale) and temperature resolution of 0.1 °C black body, depicting malignant, benign and normal pathologies are used in this study. Breast images are registered using their lower boundaries, automatically extracted using landmark points whose locations are learned during training. Boundaries are extracted using Canny edge detection and elimination of inner edges. Breast images are then segmented using fuzzy c-means clustering and the hottest regions are selected for feature extraction. Bispectral invariant features are extracted from Radon projections of these images. An Adaboost classifier is used to select and fuse the best features during training and then classify unseen test images into malignant, benign and normal classes. A data set comprising 9 malignant, 12 benign and 11 normal cases is used for evaluation of performance. Malignant cases are detected with 95% accuracy. A variant of the features using the normalized bispectrum, which discards all magnitude information, is shown to perform better for classification between benign and normal cases, with 83% accuracy compared to 66% for the original.