Examinando por Autor "Bravo, A."
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Ítem An automatic technique for left ventricle segmentation from msct cardiac volumes(IOP Publishing, 2019) Vera, M.; Medina, R.; Del Mar, A.; Arellano, J.; Huerfano, Y.; Bravo, A.In this research, an automatic technique to segment the left ventricle from the heart information in multislice computed tomography images is proposed. A preprocessing stage is considered as a necessary preliminary task for diminishing the artifacts impact in the image analysis. With this idea, a similarity enhancement that combines a smoothed version of the original volume with a processed volume using mathematical morphology is used. This preprocessing approach is compared with respect to other strategies. After, a volume-of-interest is defined in order to isolate the cavity using two cropping planes detected with least squares support vector machines. Finally, the segmentations are obtained using both a region growing algorithm and a level sets algorithm. The robustness of each enhancement strategy is validated by performing the segmentation of images. This evaluation considered the Dice score, and both volume and surface errors. A clinical dataset from 12 patients is used in the inter- and intra subject evaluation. During intra-subject validation the proposed scheme achieves the best results, while a modified version of this scheme achieved the best performance during inter-subject validation.Ítem Impacto de las Tecnologías de la información en las escuelas secundarias del sur occidente de Barranquilla(Ediciones Universidad Simón Bolívar, 2022) Berdugo, J.; Bravo, A.; Niebles, S.; Peña, J.El objetivo de este proyecto es presentar, de manera general, un análisis sobre el impacto de las tecnologías de la información sobre las instituciones educativas en el sur de la ciudad de Barranquilla, teniendo en cuenta las situaciones actuales de pandemia por las que el mundo aún sigue inmerso y las razones del porque todas las instituciones deberían empezar a enforcarse en el uso de estas. Esta investigación fue realizada teniendo en cuenta las definiciones y conceptos a trabajar, así como la importancia que radica para el mundo actual el uso de las tecnologías de la información y su impacto en los diferentes ambientes; centrándonos en el ámbito educativo y especificando como ha sido el desarrollo de las IoT en el país y en la ciudad de Barranquilla.Ítem Integrating a gradient–based difference operator with machine learning techniques in right heart segmentation(IOP Publishing, 2019) Huérfano, Y.; Vera, M.; Mar, A.; Bravo, A.In this research a three step method for right heart segmentation based on a gradient– based difference operator and machine learning techniques is reported. The proposed method is applied to human heart multi–slice computerized tomography (MSCT) volumes. The first step is the preprocessing, where a gradient–based difference operator is applied to exploit the functional relationship between the original input image and its edge enhanced version. In the second step, the least squares support vector machines (LSSVM) are used with a double purpose. First, an appropriate volume-of-interest is automatically established in order to isolate the structure to segment. Second, another LSSVM is trained for locating the voxels required for initializing the seed based clustering procedure. In the third step (segmentation step), the preprocessed volumes are subsequently processed with an unsupervised clustering technique based on simple linkage region growing. Dice score is used as a metric function to compare the segmentations obtained using the proposed method with respect to ground truth volumes traced by a cardiologist. The right atrium, pulmonary valve, right ventricle and venae cavae are segmented from 80 cardiac MSCT volumes. Reported metrics confirm that this method is a promising technique for right heart segmentation.