Santos, Selan Rodrigues dosRibeiro, ítalo Mendes da Silva2014-12-172012-02-232014-12-172011-03-02RIBEIRO, ítalo Mendes da Silva. Paralelização em GPU da segmentação vascular com extração de Centerlines por Height Ridges. 2011. 96 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal do Rio Grande do Norte, Natal, 2011.https://repositorio.ufrn.br/jspui/handle/123456789/18035The 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 Aylwardapplication/pdfAcesso AbertoComputação gráficaMedicinadiagnóstico por imagemSegmentação vascularvasos sanguíneosCenterlinesImagens medicasheight ridgesGPUArquitetura CUDAComputer graphicsMedicineDiagnostic imagingVascular segmentationBlood vesselsCenterlinesMedical imagesHeight ridgesGPUCUDAmasterThesisCNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAO