944 resultados para cancer detection


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Spatial information captured from optical remote sensors on board unmanned aerial vehicles (UAVs) has great potential in automatic surveillance of electrical infrastructure. For an automatic vision-based power line inspection system, detecting power lines from a cluttered background is one of the most important and challenging tasks. In this paper, a novel method is proposed, specifically for power line detection from aerial images. A pulse coupled neural filter is developed to remove background noise and generate an edge map prior to the Hough transform being employed to detect straight lines. An improved Hough transform is used by performing knowledge-based line clustering in Hough space to refine the detection results. The experiment on real image data captured from a UAV platform demonstrates that the proposed approach is effective for automatic power line detection.

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The application of object-based approaches to the problem of extracting vegetation information from images requires accurate delineation of individual tree crowns. This paper presents an automated method for individual tree crown detection and delineation by applying a simplified PCNN model in spectral feature space followed by post-processing using morphological reconstruction. The algorithm was tested on high resolution multi-spectral aerial images and the results are compared with two existing image segmentation algorithms. The results demonstrate that our algorithm outperforms the other two solutions with the average accuracy of 81.8%.

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A diagnosis of cancer represents a significant crisis for the child and their family. As the treatment for childhood cancer has improved dramatically over the past three decades, most children diagnosed with cancer today survive this illness. However, it is still an illness which severely disrupts the lifestyle and typical functioning of the family unit. Most treatments for cancer involve lengthy hospital stays, the endurance of painful procedures and harsh side effects. Research has confirmed that to manage and adapt to such a crisis, families must undertake measures which assist their adjustment. Variables such as level of family support, quality of parents’ marital relationship, coping of other family members, lack of other concurrent stresses and open communication within the family have been identified as influences on how well families adjust to a diagnosis of childhood cancer. Theoretical frameworks such as the Resiliency Model of Family Adjustment and Adaptation (McCubbin and McCubbin, 1993, 1996) and the Stress and Coping Model by Lazarus and Folkman (1984) have been used to explain how families and individuals adapt to crises or adverse circumstances. Developmental theories have also been posed to account for how children come to understand and learn about the concept of illness. However more descriptive information about how families and children in particular, experience and manage a diagnosis of cancer is still needed. There are still many unanswered questions surrounding how a child adapts to, understands and makes meaning from having a life-threatening illness. As a result, developing an understanding of the impact that such a serious illness has on the child and their family is crucial. A new approach to examining childhood illness such as cancer is currently underway which allows for a greater understanding of the experience of childhood cancer to be achieved. This new approach invites a phenomenological method to investigate the perspectives of those affected by childhood cancer. In the current study 9 families in which there was a diagnosis of childhood cancer were interviewed twice over a 12 month period. Using the qualitative methodology of Interpretative Phenomenological Analysis (IPA) a semi-structured interview was used to explicate the experience of childhood cancer from both the parent and child’s perspectives. A number of quantitative measures were also administered to gather specific information on the demographics of the sample population. The results of this study revealed a number of pertinent areas which need to be considered when treating such families. More importantly experiences were explicated which revealed vital phenomena that needs to be added to extend current theoretical frameworks. Parents identified the time of the diagnosis as the hardest part of their entire experience. Parents experienced an internal struggle when they were forced to come to the realization that they were not able to help their child get well. Families demonstrated an enormous ability to develop a new lifestyle which accommodated the needs of the sick child, as the sick child became the focus of their lives. Regarding the children, many of them accepted their diagnosis without complaint or question, and they were able to recognise and appreciate the support they received. Physical pain was definitely a component of the children’s experience however the emotional strain of loss of peer contact seemed just as severe. Changes over time were also noted as both parental and child experiences were often pertinent to the stage of treatment the child had reached. The approach used in this study allowed for rich and intimate detail about a sensitive issue to be revealed. Such an approach also allowed for the experience of childhood cancer on parents and the children to be more fully realised. Only now can a comprehensive and sensitive medical and psychosocial approach to the child and family be developed. For example, families may benefit from extra support at the time of diagnosis as this was identified as one of the most difficult periods. Parents may also require counselling support in coming to terms with their lack of ability to help their child heal. Given the ease at which children accepted their diagnosis, we need to question whether children are more receptive to adversity. Yet the emotional struggle children battled as a result of their illness also needs to be addressed.

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This paper describes the development and preliminary experimental evaluation of a visionbased docking system to allow an Autonomous Underwater Vehicle (AUV) to identify and attach itself to a set of uniquely identifiable targets. These targets, docking poles, are detected using Haar rectangular features and rotation of integral images. A non-holonomic controller allows the Starbug AUV to orient itself with respect to the target whilst maintaining visual contact during the manoeuvre. Experimental results show the proposed vision system is capable of robustly identifying a pair of docking poles simultaneously in a variety of orientations and lighting conditions. Experiments in an outdoor pool show that this vision system enables the AUV to dock autonomously from a distance of up to 4m with relatively low visibility.

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Aims: Influenza is commonly spread by infectious aerosols; however, detection of viruses in aerosols is not sensitive enough to confirm the characteristics of virus aerosols. The aim of this study was to develop an assay for respiratory viruses sufficiently sensitive to be used in epidemiological studies. Method: A two-step, nested real-time PCR assay was developed for MS2 bacteriophage, and for influenza A and B, parainfluenza 1 and human respiratory syncytial virus. Outer primer pairs were designed to nest each existing real-time PCR assay. The sensitivities of the nested real-time PCR assays were compared to those of existing real-time PCR assays. Both assays were applied in an aerosol study to compare their detection limits in air samples. Conclusions: The nested real-time PCR assays were found to be several logs more sensitive than the real-time PCR assays, with lower levels of virus detected at lower Ct values. The nested real-time PCR assay successfully detected MS2 in air samples, whereas the real-time assay did not. Significance and Impact of the Study: The sensitive assays for respiratory viruses will permit further research using air samples from naturally generated virus aerosols. This will inform current knowledge regarding the risks associated with the spread of viruses through aerosol transmission.

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Cancer represents a major public health concern in Australia, with 100,000 new cancer cases diagnosed each year. Physical activity level (specifically lack of physical activity) is considered a known risk factor, particularly for breast and colorectal cancers. Physical activity also plays a role following a cancer diagnosis; being regularly active during and following treatment for cancer has been associated with improvements in psychosocial and physical outcomes, as well as better compliance with treatment regimens, reduced impact of disease symptoms and treatment-related side effects, and survival benefits for particular cancers. This workshop will provide an overview of the work presented in the recently published AAESS position stand on exercise and cancer recovery. A summary of the cancer and exercise literature, in particular the purpose of exercise following diagnosis of cancer, the potential benefits derived by cancer patients and survivors from participating in exercise programs, and exercise prescription guidelines and contraindications or considerations for exercise prescription with this special population, will be given. A case summary will also be presented and discussed.

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Much of what we know about lymphoedema is derived from studies involving cancer cohorts, in particular breast cancer. Yet even within this setting, and despite the known profound physical, social and psychological effects, our understanding of associated risk factors and effectiveness of prevention and treatment strategies is poorly studied with inconsistent results. The limitations of our current methods to detect and monitor lymphoedema contribute to our lack of understanding of this condition. Current measurement approaches applied in the clinical and research setting will be described during this presentation. The strengths, limitations and practical considerations relevant to measurement methods will also be addressed. Improving the way we detect and monitor lymphoedema is necessary and critical for advancing the lymphoedema field and is relevant for the detection and monitoring of lymphoedema in the clinic as well as in research.

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The aetiology of secondary lymphoedema seems to be multifactorial, with acquired abnormalities as well as pre-existing conditions being contributory factors. Many characteristics bear inconsistent relationships to lymphoedema risk, and the few that are consistently associated with an increased risk of developing the condition, do not alone distinguish the at-risk population. Further, our current prevention and management recommendations are not backed by strong evidence. Consequently, there remains much to be learned about who gets it, how can it be prevented and how can we best treat it. Nonetheless, it is clear that lymphoedema is associated with adverse side effects, which have a profound impact on daily life, and that preliminary evidence suggests that early detection may lead to more effective treatment and lack of treatment may lead to progression. These represent important reasons as to why lymphoedema deserves clinical attention. However, several pragmatic issues must be considered when discussing whether a routine objective measure of lymphoedema could be integrated among the standard clinical care of those undertaking treatment for cancers known to be associated with the development of lymphoedema.

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Surveillance networks are typically monitored by a few people, viewing several monitors displaying the camera feeds. It is then very difficult for a human operator to effectively detect events as they happen. Recently, computer vision research has begun to address ways to automatically process some of this data, to assist human operators. Object tracking, event recognition, crowd analysis and human identification at a distance are being pursued as a means to aid human operators and improve the security of areas such as transport hubs. The task of object tracking is key to the effective use of more advanced technologies. To recognize an event people and objects must be tracked. Tracking also enhances the performance of tasks such as crowd analysis or human identification. Before an object can be tracked, it must be detected. Motion segmentation techniques, widely employed in tracking systems, produce a binary image in which objects can be located. However, these techniques are prone to errors caused by shadows and lighting changes. Detection routines often fail, either due to erroneous motion caused by noise and lighting effects, or due to the detection routines being unable to split occluded regions into their component objects. Particle filters can be used as a self contained tracking system, and make it unnecessary for the task of detection to be carried out separately except for an initial (often manual) detection to initialise the filter. Particle filters use one or more extracted features to evaluate the likelihood of an object existing at a given point each frame. Such systems however do not easily allow for multiple objects to be tracked robustly, and do not explicitly maintain the identity of tracked objects. This dissertation investigates improvements to the performance of object tracking algorithms through improved motion segmentation and the use of a particle filter. A novel hybrid motion segmentation / optical flow algorithm, capable of simultaneously extracting multiple layers of foreground and optical flow in surveillance video frames is proposed. The algorithm is shown to perform well in the presence of adverse lighting conditions, and the optical flow is capable of extracting a moving object. The proposed algorithm is integrated within a tracking system and evaluated using the ETISEO (Evaluation du Traitement et de lInterpretation de Sequences vidEO - Evaluation for video understanding) database, and significant improvement in detection and tracking performance is demonstrated when compared to a baseline system. A Scalable Condensation Filter (SCF), a particle filter designed to work within an existing tracking system, is also developed. The creation and deletion of modes and maintenance of identity is handled by the underlying tracking system; and the tracking system is able to benefit from the improved performance in uncertain conditions arising from occlusion and noise provided by a particle filter. The system is evaluated using the ETISEO database. The dissertation then investigates fusion schemes for multi-spectral tracking systems. Four fusion schemes for combining a thermal and visual colour modality are evaluated using the OTCBVS (Object Tracking and Classification in and Beyond the Visible Spectrum) database. It is shown that a middle fusion scheme yields the best results and demonstrates a significant improvement in performance when compared to a system using either mode individually. Findings from the thesis contribute to improve the performance of semi-automated video processing and therefore improve security in areas under surveillance.

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This research investigates wireless intrusion detection techniques for detecting attacks on IEEE 802.11i Robust Secure Networks (RSNs). Despite using a variety of comprehensive preventative security measures, the RSNs remain vulnerable to a number of attacks. Failure of preventative measures to address all RSN vulnerabilities dictates the need for a comprehensive monitoring capability to detect all attacks on RSNs and also to proactively address potential security vulnerabilities by detecting security policy violations in the WLAN. This research proposes novel wireless intrusion detection techniques to address these monitoring requirements and also studies correlation of the generated alarms across wireless intrusion detection system (WIDS) sensors and the detection techniques themselves for greater reliability and robustness. The specific outcomes of this research are: A comprehensive review of the outstanding vulnerabilities and attacks in IEEE 802.11i RSNs. A comprehensive review of the wireless intrusion detection techniques currently available for detecting attacks on RSNs. Identification of the drawbacks and limitations of the currently available wireless intrusion detection techniques in detecting attacks on RSNs. Development of three novel wireless intrusion detection techniques for detecting RSN attacks and security policy violations in RSNs. Development of algorithms for each novel intrusion detection technique to correlate alarms across distributed sensors of a WIDS. Development of an algorithm for automatic attack scenario detection using cross detection technique correlation. Development of an algorithm to automatically assign priority to the detected attack scenario using cross detection technique correlation.

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Objective: To assess the health-related quality of life (HRQoL) of regional and rural breast cancer survivors at 12 months post-diagnosis and to identify correlates of HRQoL. Methods: 323 (202 regional and 121 rural) Queensland women diagnosed with unilateral breast cancer in 2006/2007 participated in a population-based, cross-sectional study. HRQoL was measured using the Functional Assessment of Cancer Therapy, Breast plus arm morbidity (FACT-B+4) self-administered questionnaire. Results: In age-adjusted analyses, mean HRQoL scores of regional breast cancer survivors were comparable to their rural counterparts 12 months post-diagnosis (122.9, 95% CI: 119.8, 126.0 vs. 123.7, 95% CI: 119.7, 127.8; p>0.05). Irrespective of residence, younger (<50 years) women reported lower HRQoL than older (50+ years) women (113.5, 95% CI: 109.3, 117.8 vs. 128.2, 95%CI: 125.1, 131.2; p<0.05). Those women who received chemotherapy, reported two complications post-surgery, had poorer upper-body function than most, reported more stress, reduced coping, who were socially isolated, had no confidante for social-emotional support, had unmet healthcare needs, and low health self-efficacy reported lower HRQoL scores. Together, these factors explained 66% of the variance in overall HRQoL. The pattern of results remained similar for younger and older age groups. Conclusions and Implications: The results underscore the importance of supporting and promoting regional and rural breast cancer programs that are designed to improve physical functioning, reduce stress and provide psychosocial support following diagnosis. Further, the information can be used by general practitioners and other allied health professionals for identifying women at risk of poorer HRQoL.

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Purpose: Physical activity has become a focus of cancer recovery research as it has the potential to reduce treatment-related burden and optimize health-related quality of life (HRQoL). However, the potential for physical activity to influence recovery may be age-dependent. This paper describes physical activity levels and HRQoL among younger and older women after surgery for breast cancer and explores the correlates of physical inactivity. Methods: A population-based sample of breast cancer patients diagnosed in South-East Queensland, Australia, (n=287) were assessed once every three months, from 6 to 18 months post-surgery. The Functional Assessment of Cancer Therapy-Breast questionnaire (FACTB+4) and items from the Behavioral Risk Factor Surveillance System (BRFSS) questionnaire were used to measure HRQoL and physical activity, respectively. Physical activity was assigned metabolic equivalent task (MET) values, and categorized as < 3, 3 to 17.9 and 18+ MET-hours/weeks. Descriptive statistics, generalized linear models with age stratification (<50 years versus 50+ years), and logistic regression were used for analyses (p=0.05, two-tailed). Results: Younger women who engaged in 3 or more MET-hours/week of physical activity reported a higher HRQoL at 18 months compared to their more sedentary counterparts (p<0.05). Older women reported similar HRQoL irrespective of activity level and consistently reported clinically higher HRQoL than younger women. Increasing age, being overweight or obese, and restricting use of the treated side at six months post-surgery increased the likelihood of sedentary behavior (OR>3, p<0.05). Conclusions: Age influences the potential to observe HRQoL benefits related to physical activity participation. These results also provide relevant information for the design of exercise interventions for breast cancer survivors and highlights that some groups of women are at greater risk of long-term sedentary behavior.

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Swelling or lymphedema of the limb, trunk, or breast is considered the most problematic and dreaded concern after treatment for breast cancer and has significant physical, psychological, and social ramifications. Conservative incidence estimates suggest that 20%-30% of breast cancer survivors will experience lymphedema, with the majority of cases (up to 80%) occurring within the first year after surgery. The etiology of secondary lymphedema seems to be multifactorial, with acquired abnormalities as well as preexisting conditions being contributory factors.