Made available in DSpace on 2014-12-17T15:48:05Z (GMT). No. of bitstreams: 1 FabianoP_DISSERT.pdf: 3905877 bytes, checksum: 0721827c114aec9f61c1c690dc27dd1d (MD5) Previous issue date: 2013-04-05 / The visualization of three-dimensional(3D)images is increasigly being sed in the area of medicine, helping physicians diagnose desease. the advances achived in scaners esed for acquisition of these 3d exames, such as computerized tumography(CT) and Magnetic Resonance imaging (MRI), enable the generation of images with higher resolutions, thus, generating files with much larger sizes. Currently, the images of computationally expensive one, and demanding the use of a righ and computer for such task. The direct remote acess of these images thruogh the internet is not efficient also, since all images have to be trasferred to the user?s equipment before the 3D visualization process ca start. with these problems in mind, this work proposes and analyses a solution for the remote redering of 3D medical images, called Remote Rendering (RR3D). In RR3D, the whole hedering process is pefomed a server or a cluster of servers, with high computational power, and only the resulting image is tranferred to the client, still allowing the client to peform operations such as rotations, zoom, etc. the solution was developed using web services written in java and an architecture that uses the scientific visualization packcage paraview, the framework paraviewWeb and the PACS server DCM4CHEE.The solution was tested with two scenarios where the rendering process was performed by a sever with graphics hadwere (GPU) and by a server without GPUs. In the scenarios without GPUs, the soluction was executed in parallel with several number of cores (processing units)dedicated to it. In order to compare our solution to order medical visualization application, a third scenario was esed in the rendering process, was done locally. In all tree scenarios, the solution was tested for different network speeds. The solution solved satisfactorily the problem with the delay in the transfer of the DICOM files, while alowing the use of low and computers as client for visualizing the exams even, tablets and smart phones / A visualiza??o de imagens tridimensionais (3D) est? cada vez mais presente na ?rea da medicina, auxiliando os m?dicos no diagn?stico de doen?as e na emiss?o de laudos. Com o avan?o dos equipamentos que geram imagens tomogr?ficas dos pacientes, como os de Tomografia Computadorizada (TC), est?o sendo geradas imagens cada vez mais n?tidas e, portanto, com resolu??es e tamanhos maiores. Atualmente, as imagens contidas em um exame de TC geralmente ocupam o tamanho de dezenas e centenas de megabytes, tornando o processo de visualiza??o 3D cada vez mais pesado - exigindo do usu?rio um equipamento com bom poder computacional. O acesso remoto ? estas imagens, via internet por exemplo, tamb?m n?o ? muito eficiente, pois todas as imagens precisam ser transferidas para o equipamento do usu?rio antes que o processo de visualiza??o 3D seja iniciado. Diante destes problemas (tamanho das imagens e acesso remoto), este trabalho envolve a cria??o e an?lise de um servi?o web para renderiza??o remota de imagens m?dicas 3D, denominado RR3D. Nele, todo o processo de renderiza??o volum?trica ser? realizado por um servidor, ou cluster de servidores, com alto poder computacional e somente a imagem 3D resultante ser? enviada ao cliente, permitindo que este ainda possa fazer opera??es como rota??o, zoom etc. O servi?o web ser? desenvolvido utilizando a linguagem Java e na arquitetura do projeto ser?o utilizados o programa de visualiza??o cient?fica Paraview, o framework ParaviewWeb e o servidor DCM4CHEE

Epidemiological trends in mental disorders are shown against a background governed by medical aid health policy. The study quantitatively analyzed a dataset of mental disorders for South Africa’s leading medical aid scheme. South Africa’s leading medical aid scheme has been in operation for almost three decades. This degree of longevity allows for a reliable longitudinal analysis of diagnostic trends. Through consent of the Scheme, a database was provided, which lists mental disorder diagnoses over seven years from 2008 to mid-way through 2015. Data from this source were analyzed and interpreted. Data fields provided and made use of from the raw medical scheme database are: Date of admission (Year, Month); Patient gender; Database population per year; Patient diagnosis (DEG Description); Total per DEG Description. Each diagnosis (mental disorder) is presented in the following ways: 1. Bar charts showing the volume of specific mental illnesses each year. 2. Bar charts showing fluctuations of occurrence of a specific mental illness over time. 3. Frequency of specific mental illnesses over time, relative to the entire database population. 4. Male:Female ratio per mental disorder. 5. Female Outpatient vs. Inpatient volumes across each mental disorder and across all years (2008 – 2015).v 6. Male Outpatient vs. Inpatient volumes across each mental disorder and across all years (2008 – 2015). 7. Total number of patients per mental disorder across time (2008 – 2015). 8. Frequency polygons showing the fluctuation of a selected mental disorder over time as compared to other selected mental disorders. It is found that there are changes in prevalence rates of mental disorders over time and that these fluctuations are attributed to an economic factor within medical aid scheme cost-driven policy. The effect of cost-driven policy is that members diagnosed with a mental disorder may not be granted provision of adequate treatment because diagnosis is in part, determined by economic structures. Costs for mental illness treatment programmes are curtailed by keeping patient numbers significantly low, by radically over-diagnosing certain mental illnesses treated with comparably cheaper pharmaceuticals or by drastically curbing time spent in a mental health facility. Some members of the medical aid scheme have been deliberately misdiagnosed. Alternatively, those, correctly diagnosed, do not receive the treatment required of such an illness. The scenario then is of thousands of mentally ill people, who are not treated effectively. Members continue to pay fees, paying under the illusion that medical cover ensures effective treatment / Psychology / M.A. Psychology