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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Express?o Imuno-histoqu?mica das prote?nas GLUT-1 e HIF-1? em les?es vasculares de mucosa oral

Oliveira, Denise H?len Imaculada Pereira de 16 February 2012 (has links)
Made available in DSpace on 2014-12-17T15:32:20Z (GMT). No. of bitstreams: 1 DeniseHIPO_DISSERT.pdf: 4556175 bytes, checksum: 89c325ea02bf77fa8472508c05c7634d (MD5) Previous issue date: 2012-02-16 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / The correct histological diagnosis of vascular lesions in the oral mucosa is critical, especially in defining the treatment and prognosis, as some vascular lesions show spontaneous involution and others do not show such behavior. This study analyzed the expression immunohistochemistry of human glucose transporter protein (GLUT-1), in oral benign vascular tumors and to reclassify such lesions according to with his immunoexpression. In addition, we evaluated the immunohistochemical expression of hypoxia-inducible factor 1 alpha (HIF-1?), the main transcription factor involved in cellular adaptation to hypoxia. We analyzed 60 cases of benign oral vascular tumors: 30 cases with histological diagnosis of HEM and 30 cases of oral pyogenic granuloma (PG). The results of this research showed that of the 30 lesions initially classified as HEM, only 7 showed immuno-positivity for GLUT-1, remaining with the initial diagnosis. The remaining 23 were reclassified as vascular malformation (VM) (13 cases) and PG (10 cases). All cases in the sample with an initial diagnosis of PG were negative for GLUT-1, demonstrating the accuracy of histological diagnosis of these lesions. Concerning to the immunoexpression of HIF-1?, the Mann-Whitney test revealed a statistically significant difference between the cases of GP and MV (p = 0.002), where the median of GP (m=78) was higher than the MV (m=53). Based on these results, this study showed that a histological diagnosis alone is not always sufficient for the correct diagnosis of oral HEM and that HIF-1? participates in the pathogenesis of vascular lesions / O correto diagn?stico histol?gico de les?es vasculares em mucosa oral ? fundamental, sobretudo na hora de definir o tratamento e progn?stico, visto que algumas dessas les?es apresentam involu??o. Este trabalho analisou a express?o imunohistoqu?mica da prote?na humana transportadora de glicose (GLUT-1), em tumores vasculares benignos orais e reclassificou tais les?es de acordo com sua imunoexpress?o. Al?m disso, avaliou a express?o imuno-histoqu?mica do fator 1 induz?vel por hip?xia (HIF-1?), principal fator de transcri??o envolvido na adapta??o celular ? hip?xia. Foram analisados 60 casos de tumores vasculares benignos orais, sendo 30 casos com diagn?stico histol?gico de HEM e 30 casos de granulomas piog?nicos orais (GP). Os resultados desta pesquisa demonstraram que das 30 les?es inicialmente classificadas como HEM, apenas 7 apresentaram imuno-positividade para GLUT-1, permanecendo com o diagn?stico inicial. As 23 restantes foram reclassificadas em malforma??o vascular (MV) 13 casos e GP 10 casos . Todos os casos da amostra com diagn?stico inicial de GP apresentaram-se negativos para GLUT-1. Quanto ? imunoexpress?o do HIF-1?, o teste de Mann-Whitney revelou diferen?a estatisticamente significativa entre os casos de GP e MV(p=0,002), onde a mediana do GP (m=78) foi superior a da MV (m=53). Com base nesses resultados, este estudo mostrou que o diagn?stico histol?gico por si s? nem sempre ? suficiente para o diagn?stico correto do HEM oral e que o HIF- 1? participa da patog?nese das les?es vasculares
2

Paraleliza??o em GPU da segmenta??o vascular com extra??o de Centerlines por Height Ridges

Ribeiro, ?talo Mendes da Silva 02 March 2011 (has links)
Made available in DSpace on 2014-12-17T15:47:58Z (GMT). No. of bitstreams: 1 ItaloMSR_DISSERT.pdf: 4133389 bytes, checksum: 575496a3d8aa350df8e3e86992d9b27b (MD5) Previous issue date: 2011-03-02 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / The vascular segmentation is important in diagnosing vascular diseases like stroke and is hampered by noise in the image and very thin vessels that can pass unnoticed. One way to accomplish the segmentation is extracting the centerline of the vessel with height ridges, which uses the intensity as features for segmentation. This process can take from seconds to minutes, depending on the current technology employed. In order to accelerate the segmentation method proposed by Aylward [Aylward & Bullitt 2002] we have adapted it to run in parallel using CUDA architecture. The performance of the segmentation method running on GPU is compared to both the same method running on CPU and the original Aylward s method running also in CPU. The improvemente of the new method over the original one is twofold: the starting point for the segmentation process is not a single point in the blood vessel but a volume, thereby making it easier for the user to segment a region of interest, and; the overall gain method was 873 times faster running on GPU and 150 times more fast running on the CPU than the original CPU in Aylward / A segmenta??o vascular ? importante no diagn?stico de doen?as como o acidente vascular cerebral e ? dificultada por ru?dos na imagem e vasos muito finos que n?o s?o vistos. Uma maneira de realizar a segmenta??o ? extraindo a centerline do vaso com height ridges, que usa a intensidade como caracter?sticas para a segmenta??o. Este processo pode levar de segundos a minutos, dependendo da tecnologia atual empregada. O m?todo ? implementado em GPU, ou seja, ? executado de maneira paralela em placa gr?fica. O desempenho do m?todo de segmenta??o executado em GPU ? comparado com o mesmo m?todo em CPU e o m?todo original de Aylward em execu??o tamb?m na CPU. O melhoramento do novo m?todo sobre o original ? dupla. O ponto de partida para o processo de segmenta??o n?o ? um ?nico ponto no vaso sangu?neo, mas um volume, tornando assim mais f?cil para o usu?rio a sele??o de uma regi?o de interesse, e, o ganho do m?todo proposto foi 873 vezes mais r?pido sendo executado em GPU e 150 vezes mais r?pido sendo executado em CPU do que o original de Aylward em CPU

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