12 resultados para Region growing algorithms
em Deakin Research Online - Australia
Resumo:
Lung modelling has emerged as a useful method for diagnosing lung diseases. Image segmentation is an important part of lung modelling systems. The ill-defined nature of image segmentation makes automated lung modelling difficult. Also, low resolution of lung images further increases the difficulty of the lung image segmentation. It is therefore important to identify a suitable segmentation algorithm that can enhance lung modelling accuracies. This paper investigates six image segmentation algorithms, used in medical imaging, and also their application to lung modelling. The algorithms are: normalised cuts, graph, region growing, watershed, Markov random field, and mean shift. The performance of the six segmentation algorithms is determined through a set of experiments on realistic 2D CT lung images. An experimental procedure is devised to measure the performance of the tested algorithms. The measured segmentation accuracies as well as execution times of the six algorithms are then compared and discussed.
Resumo:
The thickness of the retinal nerve fiber layer (RFNL) has become a diagnose measure for glaucoma assessment. To measure this thickness, accurate segmentation of the RFNL in optical coherence tomography (OCT) images is essential. Identification of a suitable segmentation algorithm will facilitate the enhancement of the RNFL thickness measurement accuracy. This paper investigates the performance of six algorithms in the segmentation of RNFL in OCT images. The algorithms are: normalised cuts, region growing, k-means clustering, active contour, level sets segmentation: Piecewise Gaussian Method (PGM) and Kernelized Method (KM). The performance of the six algorithms are determined through a set of experiments on OCT retinal images. An experimental procedure is used to measure the performance of the tested algorithms. The measured segmentation precision-recall results of the six algorithms are compared and discussed.
Resumo:
Pixel-scale fine details are often lost during image processing tasks such as image reduction and filtering. Block or region based algorithms typically rely on averaging functions to implement the required operation and traditional function choices struggle to preserve small, spatially cohesive clusters of pixels which may be corrupted by noise. This article proposes the construction of fuzzy measures of cluster compactness to account for the spatial organisation of pixels. We present two construction methods (minimum spannning trees and fuzzy measure decomposition) to generate measures with specific properties: monotonicity with respect to cluster size; invariance with respect to translation, reflection and rotation; and, discrimination between pixel sets of fixed cardinality with different spatial arrangements. We apply these measures within a non-monotonic mode-like averaging function used for image reduction and we show that this new function preserves pixel-scale structures better than existing monotonie averages.
Resumo:
The Asia-Pacific region is undergoing a major change in both food and health patterns, with a connection between the two more than likely. Evidence for certain traditional Asia-Pacific foods as protective agents against chronic non-communicable disease and cardiovascular disease (CVD), in particular, is growing at a time when their usage diminishes. The nature of the evidence to establish relevant Asia-Pacific food-health linkages will include randomised placebo-controlled clinical trials, but is much more extensive and meaningful. Okinawans have probably achieved one of the most successful food cultures from a health point of view and serve as a reference point for the Asia-Pacific region. The expert working party has produced, in November 2000, the 'Okinawan Recommendations on Nutrition and CVD in the Asia-Pacific region'.
Resumo:
Growing self-organizing map (GSOM) has been characterized as a knowledge discovery visualization application which outshines the traditional self-organizing map (SOM) due to its dynamic structure in which nodes can grow based on the input data. GSOM is utilized as a visualization tool in this paper to cluster fMRI finger tapping and non- tapping data, demonstrating the visualization capability to distinguish between tapping or non-tapping. A unique feature of GSOM is a parameter called the spread factor whose functionality is to control the spread of the GSOM map. By setting different levels of spread factor, different granularities of region of interests within tapping or non-tapping images can be visualized and analyzed. Euclidean distance based similarity calculation is used to quantify the visualized difference between tapping and non tapping images. Once the differences are identified, the spread factor is used to generate a more detailed view of those regions to provide a better visualization of the brain regions.
Resumo:
Food security is a significant issue in the remote, high altitude areas of Nepal. Malnutrition is common because the harsh climate restricts production and access to fresh food. Humla is a province in north-west Nepal where the severe weather conditions and limited arable land restrict the growing season of vegetables to only 4-5 months a year. Passive solar greenhouses are a technology that can be used to extend the growing period of vegetables. For the greenhouse to be effective in Humla, the design must be appropriate to the climatic conditions, available resources and the social requirements of the community. This paper describes the design and evaluation of a family-sized solar greenhouse proposed for Humla. Three solar greenhouses built in other high altitude areas have initially been reviewed to see what techniques might be replicated in Humla. The thermal performance of the proposed family-sized greenhouse has been predicted using the solar simulation software, TRNSYS, and compared against an existing design in the area. The proposed design was found to be superior and average night-time temperatures in the coldest month were predicted to be approximately 7°C higher. Overheating was controlled in the hottest month by shading and natural ventilation.
Resumo:
Youth, Media and Culture in the Asia Pacific Region presents an analysis of youth media activities in a diverse, but geographically connected Asia Pacific region. The region, which is spatially connected by its colonial and imperial past, is becoming a significant player in the globalized world. In this context, youth situated in these economically, politically and socially structured communities are redefining their locales through their patterns of media use. The discourse of ‘youth’ in this disparate region is manifest in the media through their identity articulations and social activism. The book illustrates that these ‘youth subcultures’ in the Asia Pacific are part of the well marketed global consumerism culture, and yet at other times independent of the commodifying impetus of global capital. It draws on case studies to examine some of the media practices youth in the region are engaged in and elucidates the process of social change taking place in some Asia Pacific nations.
'This book contributes to the important and growing field of youth media studies. The regionalization of media research is necessarily recuperated here, bringing large populations of media users into a frame of reference that allows critical reflection on the new waves of use and sociality in the Asia Pacific region.'
Resumo:
The internet age has fuelled an enormous explosion in the amount of information generated by humanity. Much of this information is transient in nature, created to be immediately consumed and built upon (or discarded). The field of data mining is surprisingly scant with algorithms that are geared towards the unsupervised knowledge extraction of such dynamic data streams. This chapter describes a new neural network algorithm inspired by self-organising maps. The new algorithm is a hybrid algorithm from the growing self-organising map (GSOM) and the cellular probabilistic self-organising map (CPSOM). The result is an algorithm which generates a dynamically growing feature map for the purpose of clustering dynamic data streams and tracking clusters as they evolve in the data stream.
Resumo:
The phenomenal growth in economy experienced in developed countries throughout the 20th century has largely been driven by the availability of conventional energy sources for electricity generation. However, increased concern about fossil fuels and adverse effect of carbon dioxide emission in to atmosphere changed the conventional power system to a viable one by integrating renewable energy sources into the existing system. Among the Renewable Energy (RE) sources, wind energy is one of the fastest growing technologies in reducing the Green House Gas (GHG) emissions in to the atmosphere due to its continuous availability throughout a period. Hence, this paper discusses the performance of a wind-grid connected system in a semi-arid region by conducting a case study. Wilson promontory, one of the best locations for wind generation in Victoria is considered as a case study. Hybrid Optimization Model for Electric Renewable (HOMER) is used as a simulating tool for this analysis. This study also presents the influences of storage system in the proposed Hybrid Power System (HPS) allowing energy to be stored during higher generations or lower load demands. In addition this paper also discusses the major integration issues to facilitate the large scale wind energy into the grid for reliable power generation and distribution.
Resumo:
Continuous usage of fossil fuels and other conventional resources to meet the growing demand has resulted in in-creased energy crisis and greenhouse gas emissions. Hence, it is essential to use renewable energy sources for more reliable, effective, sustainable and pollution free transmission and distribution networks. Therefore, to facilitate large-scale integration of renewable energy in particular wind and solar photovoltaic (PV) energy, this paper presents the feasibility analysis for semi-arid climate and finds the most suitable places in North East region of Victoria for re-newable energy generation. For economic and environmental analysis, Hybrid Optimization Model for Electric Re-newables (HOMER) has used to investigate the prospects of wind and solar energy considering the Net Present Cost (NPC), Cost of Energy (COE) and Renewable fraction (RF). Six locations are selected from North East region of Victo-ria and simulations are performed. From the feasibility analysis, it can be concluded that Mount Hotham is one of the most suitable locations for wind energy generation while Wangaratta is the most suitable location for solar energy generation. Mount Hotham is also the best suitable locations in North East region for hybrid power systems i.e., com-bination of both wind and solar energy generation.
Resumo:
BACKGROUND: In the Arkhangelsk region of Northern Russia, multidrug-resistant (MDR) tuberculosis (TB) rates in new cases are amongst the highest in the world. In 2014, MDR-TB rates reached 31.7% among new cases and 56.9% among retreatment cases. The development of new diagnostic tools allows for faster detection of both TB and MDR-TB and should lead to reduced transmission by earlier initiation of anti-TB therapy. STUDY AIM: The PROVE-IT (Policy Relevant Outcomes from Validating Evidence on Impact) Russia study aimed to assess the impact of the implementation of line probe assay (LPA) as part of an LPA-based diagnostic algorithm for patients with presumptive MDR-TB focusing on time to treatment initiation with time from first-care seeking visit to the initiation of MDR-TB treatment rather than diagnostic accuracy as the primary outcome, and to assess treatment outcomes. We hypothesized that the implementation of LPA would result in faster time to treatment initiation and better treatment outcomes.
METHODS: A culture-based diagnostic algorithm used prior to LPA implementation was compared to an LPA-based algorithm that replaced BacTAlert and Löwenstein Jensen (LJ) for drug sensitivity testing. A total of 295 MDR-TB patients were included in the study, 163 diagnosed with the culture-based algorithm, 132 with the LPA-based algorithm.
RESULTS: Among smear positive patients, the implementation of the LPA-based algorithm was associated with a median decrease in time to MDR-TB treatment initiation of 50 and 66 days compared to the culture-based algorithm (BacTAlert and LJ respectively, p<0.001). In smear negative patients, the LPA-based algorithm was associated with a median decrease in time to MDR-TB treatment initiation of 78 days when compared to the culture-based algorithm (LJ, p<0.001). However, several weeks were still needed for treatment initiation in LPA-based algorithm, 24 days in smear positive, and 62 days in smear negative patients. Overall treatment outcomes were better in LPA-based algorithm compared to culture-based algorithm (p = 0.003). Treatment success rates at 20 months of treatment were higher in patients diagnosed with the LPA-based algorithm (65.2%) as compared to those diagnosed with the culture-based algorithm (44.8%). Mortality was also lower in the LPA-based algorithm group (7.6%) compared to the culture-based algorithm group (15.9%). There was no statistically significant difference in smear and culture conversion rates between the two algorithms.
CONCLUSION: The results of the study suggest that the introduction of LPA leads to faster time to MDR diagnosis and earlier treatment initiation as well as better treatment outcomes for patients with MDR-TB. These findings also highlight the need for further improvements within the health system to reduce both patient and diagnostic delays to truly optimize the impact of new, rapid diagnostics.
Resumo:
BACKGROUND: The maternal health system in Ethiopia links health posts in rural communities (kebeles) with district (woreda) health centres, and health centres with primary hospitals. At each health post two Health Extension Workers (HEWs) assist women with birth preparedness, complication readiness, and mobilize communities to facilitate timely referral to mid-level service providers. This study explored HEWs' and mother's attitudes to maternal health services in Adwa Woreda, Tigray Region. METHODS: In this qualitative study, we trained 16 HEWs to interview 45 women to gain a better understanding of the social context of maternal health related behaviours. Themes included barriers to health services; women's social status and mobility; and women's perceptions of skilled birth attendant's care. All data were analyzed thematically. FINDINGS: There have been substantial efforts to improve maternal health and reduce maternal mortality in Adwa Woreda. Women identified barriers to healthcare including distance and lack of transportation due to geographical factors; the absence of many husbands due to off-woreda farming; traditional factors such as zwar (some pregnant women are afraid of meeting other pregnant women), and discouragement from mothers and mothers-in-law who delivered their children at home. Some women experienced disrespectful care at the hospital. Facilitators to skilled birth attendance included: identification of pregnant women through Women's Development Groups (WDGs), and referral by ambulance to health facilities either before a woman's Expected Due Date (EDD) or if labour started at home. CONCLUSION: With the support of WDGs, HEWs have increased the rate of skilled birth attendance by calling ambulances to transfer women to health centres either before their EDD or when labour starts at home. These findings add to the growing body of evidence that health workers at the community level can work with women's groups to improve maternal health, thus reducing the need for emergency obstetric care in low-income countries.