Automatic image scaling for place recognition in changing environments

Robustness to variations in environmental conditions and camera viewpoint is essential for long-term place recognition, navigation and SLAM. Existing systems typically solve either of these problems, but invariance to both remains a challenge. This paper presents a training-free approach to lateral viewpoint- and condition-invariant, vision-based place recognition. Our successive frame patch-tracking technique infers average scene depth along traverses and automatically rescales views of the same place at different depths to increase their similarity. We combine our system with the condition-invariant SMART algorithm and demonstrate place recognition between day and night, across entire 4-lane-plus-median-strip roads, where current algorithms fail.

Women's perceptions of communication in pregnancy and childbirth: Influences on participation and satisfaction with care

In this study, 3531 Queensland women, who had recently given birth, completed a questionnaire that included questions about their participation in decision making during pregnancy, their ratings of client centred care and perceived quality of care. These data tested a version of Street’s (2001) linguistic model of patient participation in care (LMOPPC), adapted to the maternity context. We investigated how age and education influenced women’s perceptions of their participation and quality of care. Hierarchical multiple regressions revealed that women’s perceived ability to make decisions, and the extent of client-centred communication with maternity care providers were the most influential predictors of participation and perceived quality of care. Participation in care predicted perceived quality of care, but the influence of client-centred communication by a care provider and a woman’s confidence in decision making were stronger predictors of perceived quality of care. Age and education level were not important predictors. These findings extend and support the use of LMOPPC in the maternity context.

Job satisfaction, stress and burnout in haemodialysis nurses

Haemodialysis nurses provide health care for people with end stage kidney disease leading to a unique, intense and complex interaction between nurses and patients. This study involved the development of a model which explains the relationships between the work environment, job satisfaction, stress and burnout of haemodialysis nurses in Australia and New Zealand. Results from this study identified that haemodialysis nurses, while being satisfied by their jobs, were also experiencing high levels of burnout. This study's novel contribution could lead to improving the retention of the nursing workforce which is crucial due to the growing global burden of chronic disease.

Quantitative genetic modeling of lateral ventricular shape and volume using multi-atlas fluid image alignment in twins

Despite substantial progress in measuring the 3D profile of anatomical variations in the human brain, their genetic and environmental causes remain enigmatic. We developed an automated system to identify and map genetic and environmental effects on brain structure in large brain MRI databases . We applied our multi-template segmentation approach ("Multi-Atlas Fluid Image Alignment") to fluidly propagate hand-labeled parameterized surface meshes into 116 scans of twins (60 identical, 56 fraternal), labeling the lateral ventricles. Mesh surfaces were averaged within subjects to minimize segmentation error. We fitted quantitative genetic models at each of 30,000 surface points to measure the proportion of shape variance attributable to (1) genetic differences among subjects, (2) environmental influences unique to each individual, and (3) shared environmental effects. Surface-based statistical maps revealed 3D heritability patterns, and their significance, with and without adjustments for global brain scale. These maps visualized detailed profiles of environmental versus genetic influences on the brain, extending genetic models to spatially detailed, automatically computed, 3D maps.

Automated ventricular mapping with multi-atlas fluid image alignment reveals genetic effects in Alzheimer's disease

We developed and validated a new method to create automated 3D parametric surface models of the lateral ventricles in brain MRI scans, providing an efficient approach to monitor degenerative disease in clinical studies and drug trials. First, we used a set of parameterized surfaces to represent the ventricles in four subjects' manually labeled brain MRI scans (atlases). We fluidly registered each atlas and mesh model to MRIs from 17 Alzheimer's disease (AD) patients and 13 age- and gender-matched healthy elderly control subjects, and 18 asymptomatic ApoE4-carriers and 18 age- and gender-matched non-carriers. We examined genotyped healthy subjects with the goal of detecting subtle effects of a gene that confers heightened risk for Alzheimer's disease. We averaged the meshes extracted for each 3D MR data set, and combined the automated segmentations with a radial mapping approach to localize ventricular shape differences in patients. Validation experiments comparing automated and expert manual segmentations showed that (1) the Hausdorff labeling error rapidly decreased, and (2) the power to detect disease- and gene-related alterations improved, as the number of atlases, N, was increased from 1 to 9. In surface-based statistical maps, we detected more widespread and intense anatomical deficits as we increased the number of atlases. We formulated a statistical stopping criterion to determine the optimal number of atlases to use. Healthy ApoE4-carriers and those with AD showed local ventricular abnormalities. This high-throughput method for morphometric studies further motivates the combination of genetic and neuroimaging strategies in predicting AD progression and treatment response. © 2007 Elsevier Inc. All rights reserved.

MR image-based measurement of rates of change in volumes of brain structures. Part II: Application to a study of Alzheimer's disease and normal aging

We present global and regional rates of brain atrophy measured on serially acquired Tl-weighted brain MR images for a group of Alzheimer's disease (AD) patients and age-matched normal control (NC) subjects using the analysis procedure described in Part I. Three rates of brain atrophy: the rate of atrophy in the cerebrum, the rate of lateral ventricular enlargement and the rate of atrophy in the region of temporal lobes, were evaluated for 14 AD patients and 14 age-matched NC subjects. All three rates showed significant differences between the two groups. However, the greatest separation of the two groups was obtained when the regional rates were combined. This application has demonstrated that rates of brain atrophy, especially in specific regions of the brain, based on MR images can provide sensitive measures for evaluating the progression of AD. These measures will be useful for the evaluation of therapeutic effects of novel therapies for AD.

Linking client and employee perceptions of the organization: A study of client satisfaction with health care services

Client satisfaction with health care services has usually been researched in terms of socio-demographic and predispositional characteristics associated with the client. The present study included organizational characteristics as predictors of client satisfaction with health care services. Participants in the research were clients and employees of an Australian public-sector health care organization who responded to separate client and employee questionnaires. Hierarchical regression analyses indicated that, after controlling for a number of client characteristics, organizational characteristics, as perceived by employees, accounted for a significant proportion of additional variance in client satisfaction with health care services. Results of the present study provided some support for the proposition that employee perceptions of the working environment should be considered in a more comprehensive understanding of client satisfaction with health care services. Limitations of the study highlight practical difficulties in the assessment of client outcomes and methodological complexities in linking individual and organizational processes.

A longitudinal investigation of coping processes during a merger: Implications for job satisfaction and organizational identification

This study tested the utility of a stress and coping model of employee adjustment to a merger. Two hundred and twenty employees completed both questionnaires (Time 1: 3 months after merger implementation; Time 2: 2 years later). Structural equation modeling analyses revealed that positive event characteristics predicted greater appraisals of self-efficacy and less stress at Time 1. Self-efficacy, in turn, predicted greater use of problem-focused coping at Time 2, whereas stress predicted a greater use of problem-focused and avoidance coping. Finally, problem-focused coping predicted higher levels of job satisfaction and identification with the merged organization (Time 2), whereas avoidance coping predicted lower identification.

Birdcall retrieval from environmental acoustic recordings using image processing

Acoustic recordings of the environment provide an effective means to monitor bird species diversity. To facilitate exploration of acoustic recordings, we describe a content-based birdcall retrieval algorithm. A query birdcall is a region of spectrogram bounded by frequency and time. Retrieval depends on a similarity measure derived from the orientation and distribution of spectral ridges. The spectral ridge detection method caters for a broad range of birdcall structures. In this paper, we extend previous work by incorporating a spectrogram scaling step in order to improve the detection of spectral ridges. Compared to an existing approach based on MFCC features, our feature representation achieves better retrieval performance for multiple bird species in noisy recordings.

Scalable Bayesian Computation for intractable likelihoods in image analysis

The inverse temperature hyperparameter of the hidden Potts model governs the strength of spatial cohesion and therefore has a substantial influence over the resulting model fit. The difficulty arises from the dependence of an intractable normalising constant on the value of the inverse temperature, thus there is no closed form solution for sampling from the distribution directly. We review three computational approaches for addressing this issue, namely pseudolikelihood, path sampling, and the approximate exchange algorithm. We compare the accuracy and scalability of these methods using a simulation study.

Evaluation of a mobile phone image-based dietary assessment method in adults with type 2 diabetes

Photographic and image-based dietary records have limited evidence evaluating their performance and use among adults with a chronic disease. This study evaluated the performance of a mobile phone image-based dietary record, the Nutricam Dietary Assessment Method (NuDAM), in adults with type 2 diabetes mellitus (T2DM). Criterion validity was determined by comparing energy intake (EI) with total energy expenditure (TEE) measured by the doubly-labelled water technique. Relative validity was established by comparison to a weighed food record (WFR). Inter-rater reliability was assessed by comparing estimates of intake from three dietitians. Ten adults (6 males, age=61.2±6.9 years, BMI=31.0±4.5 kg/m2) participated. Compared to TEE, mean EI was under-reported using both methods, with a mean ratio of EI:TEE 0.76±0.20 for the NuDAM and 0.76±0.17 for the WFR. There was moderate to high correlations between the NuDAM and WFR for energy (r=0.57), carbohydrate (r=0.63, p<0.05), protein (r=0.78, p<0.01) and alcohol (rs=0.85, p<0.01), with a weaker relationship for fat (r=0.24). Agreement between dietitians for nutrient intake for the 3-day NuDAM (ICC = 0.77-0.99) was marginally lower when compared with the 3-day WFR (ICC=0.82-0.99). All subjects preferred using the NuDAM and were willing to use it again for longer recording periods.

Factors influencing radiation therapy student clinical placement satisfaction

Introduction Radiation therapy students at Queensland University of Technology (QUT) attend clinical placements at five different clinical departments with varying resources and support strategies. This study aimed to determine the relative availability and perceived importance of different factors affecting student support while on clinical placement. The purpose of the research was to inform development of future support mechanisms to enhance radiation therapy students’ experience on clinical placement. Methods This study used anonymous Likert-style surveys to gather data from years 1 and 2 radiation therapy students from QUT and clinical educators from Queensland relating to availability and importance of support mechanisms during clinical placements in a semester. Results The study findings demonstrated student satisfaction with clinical support and suggested that level of support on placement influenced student employment choices. Staff support was perceived as more important than physical resources; particularly access to a named mentor, a clinical educator and weekly formative feedback. Both students and educators highlighted the impact of time pressures. Conclusions The support offered to radiation therapy students by clinical staff is more highly valued than physical resources or models of placement support. Protected time and acknowledgement of the importance of clinical education roles are both invaluable. Joint investment in mentor support by both universities and clinical departments is crucial for facilitation of effective clinical learning.

PREPARE Study: Patient satisfaction survey with care provided in the low clearance clinic

Background Formalised predialysis care has been shown to extend the wellness of individuals with advanced chronic kidney disease, slow disease progression and increase the uptake of home dialysis. Predialysis care, incorporating multidisciplinary input is also vital in delaying the onset of end-stage kidney disease and reducing hospital admissions; thereby decreasing financial demands on health budgets. Predialysis care should include comprehensive information provision and predialysis education. This empowers patients to choose self-care strategies and therapies.

Identity, image, and sexuality in young adults with cancer

The impact of disease and treatment on a young adult's self-image and sexuality has been largely overlooked. This is surprising given that establishing social and romantic relationships is a normal occurrence in young adulthood. This article describes three female patients' cancer journeys and demonstrates how their experiences have impacted their psychosocial function and self-regard. The themes of body image, self-esteem, and identity formation are explored, in relation to implications for relationship-building and moving beyond a cancer diagnosis. This article has been written by young cancer survivors, Danielle Tindle, Kelly Denver, and Faye Lilley, in an effort to elucidate the ongoing struggle to reconcile cancer into a normal young adult's life.

Image processing and classification procedure for the analysis of Australian frog vocalisations

Frog species have been declining worldwide at unprecedented rates in the past decades. There are many reasons for this decline including pollution, habitat loss, and invasive species [1]. To preserve, protect, and restore frog biodiversity, it is important to monitor and assess frog species. In this paper, a novel method using image processing techniques for analyzing Australian frog vocalisations is proposed. An FFT is applied to audio data to produce a spectrogram. Then, acoustic events are detected and isolated into corresponding segments through image processing techniques applied to the spectrogram. For each segment, spectral peak tracks are extracted with selected seeds and a region growing technique is utilised to obtain the contour of each frog vocalisation. Based on spectral peak tracks and the contour of each frog vocalisation, six feature sets are extracted. Principal component analysis reduces each feature set down to six principal components which are tested for classification performance with a k-nearest neighbor classifier. This experiment tests the proposed method of classification on fourteen frog species which are geographically well distributed throughout Queensland, Australia. The experimental results show that the best average classification accuracy for the fourteen frog species can be up to 87%.