Examinando por Autor "Vivas, Marisela"
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Ítem Assessment of methods for volumetric quantification of intracerebral hematomas in computerized tomography images(Sociedad Venezolana de Farmacología Clínica y Terapéutica, 2018) Vera, Miguel; Huérfano, Yoleidy; Barrera, Doris; Valbuena, Oscar; Salazar, Williams; Vera, María Isabel; Hernández, Carlos; Vivas, Marisela; Borrero, Maryury; Molina, Ángel Valentín; Martínez, Luis Javier; Salazar, Juan; Gelvez, Elkin; Contreras, Yudith; Sáenz, FrankThis work evaluates the performance of computational methods aimed at volume generation of five intracerebral hematomas (ICH), present in multi-layer computed tomography images, by means of three complementary steps. First. A ground truth volume or reference volume (RV) is considered. This RV is obtained, by a neurosurgeon, using the manual planimetric method (MPM). In a second step, the volumetry of the 5 ICH’s is obtained considering both the original version of the ABC/2 method and two of its variants, identified in this paper as ABC/3 method and 2ABC/3 method. The ABC methods allow for calculating hematoma volume under the geometric assumption that the ICH has an ellipsoidal shape. In a third step, a smart automatic technique (SAT) is implemented to generate the three-dimensional segmentation of each ICH. In the context of the present work, the expression SAT method is used to refer to the new methodology proposed to calculate the volume of the ICH. In order to evaluate the performance of the SAT, the Dice coefficient (Dc) is used to compare the dilated segmentations of the ICH with the ICH segmentations generated, manually, by a neurosurgeon. Finally, the percentage relative error is calculated as a measure to evaluate the methodologies considered. The results show that the SAT method exhibits the best performance, generating an average percentage error of less than 3%.Ítem Automatic segmentation of a cerebral glioblastoma using a smart computational technique(Sociedad Venezolana de Farmacología Clínica y Terapéutica, 2018) Vera, Miguel; Huérfano, Yoleidy; Valbuena, Oscar; Hoyos, Diego; Arias, Yeni; Contreras, Yudith; Salazar, Williams; Vera, María Isabel; Borrero, Maryury; Vivas, Marisela; Hernández, Carlos; Barrera, Doris; Molina, Ángel Valentín; Martínez, Luis Javier; Salazar, Juan; Gelvez, ElkinWe propose an intelligent computational technique for the image segmentation of a type IV brain tumor, identified as multiform glioblastoma (MGB), which is present in multi-layer computed tomography images. This technique consists of 3 stages developed in the three-dimensional domain. They are: pre-processing, segmentation and validation. During the validation stage, the Dice coefficient (Dc) is considered in order to compare the segmentations of the MGB, obtained automatically, with the segmentations of the MGB generated manually, by a neuro-oncologist. The combination of parameters linked to the highest Dc, allows to establish the optimal parameters of each of the computational algorithms that make up the proposed nonlinear technique. The obtained results allow to report a Dc higher than 0.88, validating a good correlation between the manual segmentations and those produced by the computational technique developed.Ítem Automatic segmentation of a meningioma using a computational technique in magnetic resonance imaging(Sociedad Venezolana de Farmacología Clínica y Terapéutica, 2018) Vera, Miguel; Huérfano, Yoleidy; Molina, Ángel Valentín; Valbuena, Oscar; Vivas, Marisela; Cuberos, María; Salazar, Williams; Vera, María Isabel; Borrero, Maryury; Hernández, Carlos; Barrera, Doris; Martínez, Luis Javier; Salazar, Juan; Gelvez, Elkin; Contreras, Yudith; Sáenz, FrankThrough this work we propose a computational technique for the segmentation of a brain tumor, identified as meningioma (MGT), which is present in magnetic resonance images (MRI). This technique consists of 3 stages developed in the three-dimensional domain: pre-processing, segmentation and post-processing. The percent relative error (PrE) is considered to compare the segmentations of the MGT, generated by a neuro-oncologist manually, with the dilated segmentations of the MGT, obtained automatically. The combination of parameters linked to the lowest PrE, provides the optimal parameters of each computational algorithm that makes up the proposed computational technique. Results allow reporting a PrE of 1.44%, showing an excellent correlation between the manual segmentations and those produced by the computational technique developed.Ítem Automatic segmentation of epidural hematomas using a computational technique based on intelligent operators: a clinical utility(Sociedad Venezolana de Farmacología Clínica y Terapéutica, 2018) Salazar, Juan; Vera, Miguel; Huérfano, Yoleidy; Valbuena, Oscar; Salazar, Williams; Vera, María Isabel; Gelvez, Elkin; Contreras, Yudith; Borrero, Maryury; Vivas, Marisela; Barrera, Doris; Hernández, Carlos; Molina, Ángel Valentín; Martínez, Luis Javier; Sáenz, FrankThis paper proposes a non-linear computational technique for the segmentation of epidural hematomas (EDH), present in 7 multilayer computed tomography brain imaging databases. This technique consists of 3 stages developed in the three-dimensional domain, namely: pre-processing, segmentation and quantification of the volume occupied by each of the segmented EDHs. To make value judgments about the performance of the proposed technique, the EDH dilated segmentations, obtained automatically, and the EDH segmentations, generated manually by a neurosurgeon, are compared using the Dice coefficient (Dc). The combination of parameters linked to the highest Dc value, defines the optimal parameters of each of the computational algorithms that make up the proposed nonlinear technique. The obtained results allow the reporting of a Dc superior to 0.90 which indicates a good correlation between the manual segmentations and those produced by the computational technique developed. Finally, as an immediate clinical application, considering the automatic segmentations, the volume of each hematoma is calculated considering both the voxel size of each database and the number of voxels that make up the segmented hematomas.Ítem Digital processing of medical images: application in synthetic cardiac datasets using the CRISP_DM methodology(Sociedad Latinoamericana de Hipertensión, 2018) Contreras, Yudith; Vera, Miguel; Huérfano, Yoleidy; Valbuena, Oscar; Salazar, Williams; Vera, María Isabel; Borrero, Maryury; Barrera, Doris; Hernández, Carlos; Molina, Ángel Valentín; Martínez, Luis Javier; Sáenz, Frank; Vivas, Marisela; Salazar, Juan; Gelvez, ElkinIn this work an adaptation of the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology, in the context of digital medical image processing is proposed. Specifically, synthetic images reported in the literature are used as numerical phantoms. Construction of the synthetic images was inspired by a detailed analysis of some of the imperfections found in the real multilayer cardiac computed tomography images. Of all the imperfections considered, only Poisson noise was selected and incorporated into a synthetic database. An example is presented in which images contaminated with Poisson noise are processed and then subject to two classical digital smoothing techniques, identified as Gaussian filter and anisotropic diffusion filter. Additionally, the peak of the signal-to-noise ratio (PSNR) is considered as a metric to analyze the performance of these filters.Ítem Low grade glioma segmentation using an automatic computational technique in magnetic resonance imaging(Sociedad Venezolana de Farmacología Clínica y Terapéutica, 2018) Vera, Miguel; Huérfano, Yoleidy; Valbuena, Oscar; Contreras, Yudith; Cuberos, María; Vivas, Marisela; Salazar, Williams; Vera, María Isabel; Borrero, Maryury; Hernández, Carlos; Barrera, Doris; Molina, Ángel Valentín; Martínez, Luis Javier; Salazar, Juan; Gelvez, Elkin; Sáenz, FrankThrough this work we propose a computational technique for the segmentation of a brain tumor, identified as low grade glioma (LGG), specifically grade II astrocytoma, which is present in magnetic resonance images (MRI). This technique consists of 3 stages developed in the three-dimensional domain. They are: pre-processing, segmentation and postprocessing. The percent relative error (PrE) is considered to compare the segmentations of the LGG, generated by a neuro- oncologist manually, with the dilated segmentations of the LGG, obtained automatically. The combination of parameters linked to the lowest PrE, allow establishing the optimal parameters of each computational algorithm that makes up the proposed computational technique. The results allow reporting a PrE of 1.43%, which indicates an excellent correlation between the manual segmentations and those produced by the computational technique developed.Ítem Segmentación de la válvula pulmonar a partir de imágenes de tomografía cardiaca usando una estrategia basada en realce por similaridad local(Cooperativa servicios y suministros 212518 RS, 2017) Vera, Miguel; Huérfano, Yoleidy; Contreras-Velásquez, Julio; Bermúdez, Valmore; Del Mar, Atilio; Cuberos, María; Vivas, Marisela; Bautista, Nahid; Saenz, Frank; Rodriguez, JhoelEn el siguiente artículo se da a conocer el uso de la estrategia similaridad local, en la segmentación tridimensional (3D) de la válvula pulmonar en 20 imágenes cardiacas de tomografía computarizada multicapa, correspondientes al ciclo cardiaco completo de un sujeto. La estrategia consta de las siguientes etapas: a) pre-procesamiento, b) segmentación y c) entonación de parámetros. La etapa a) se aplica, preliminarmente al instante de diástole final y se divide en dos fases denominadas: Filtrado y Definición de una región de interés (ROI) y se emplea la técnica denominada realce por similaridad local (LSE). La aplicación de estas fases tiene por finalidad abordar los problemas de ruido, artefactos y bajo contraste que poseen las mencionadas imágenes. La etapa b) permite la segmentación de la válvula pulmonar, mediante un algoritmo de agrupamiento denominado crecimiento de regiones (RG) el cual es aplicado a las imágenes pre-procesadas. El RG es inicializado con un vóxel “semilla” el cual es detectado mediante un operador de inteligencia artificial denominado máquinas de soporte vectorial de mínimos cuadrados (LSSVM). Finalmente, durante la etapa c), una métrica denominada coeficiente de Dice (Dc) es utilizada para comparar las segmentaciones obtenidas mediante la estrategia propuesta y la segmentación generada, manualmente, por un cardiólogo. La combinación de técnicas de filtrado que genera el Dc más elevado considerando el instante de diástole se aplica posteriormente a las 19 imágenes 3D restantes, obteniéndose un Dc promedio comparable con el reportado en la literatura especializada.Ítem Smoothing filters in synthetic cerebral magnetic resonance images: A comparative study(Sociedad Latinoamericana de Hipertensión, 2018) Gelvez, Elkin; Vera, Miguel; Huérfano, Yoleidy; Valbuena, Oscar; Salazar, Williams; Vera, María Isabel; Borrero, Maryury; Barrera, Doris; Hernández, Carlos; Molina, Ángel Valentín; Martínez, Luis Javier; Sáenz, Frank; Vivas, Marisela; Contreras, Julio; Restrepo, Jorge; Vanegas, Juan; Salazar, Juan; Contreras, YudithThis paper presents the evaluation of two computational techniques for smoothing noise that might be present in synthetic images or numerical phantoms of magnetic resonance (MRI). The images that will serve as the databases (DB) during the course of this evaluation are available freely on the Internet and are reported in specialized literature as synthetic images called BrainWeb. The images that belong to this DB were contaminated with Rician noise, this being the most frequent type of noise in real MRI images. Also, the techniques that are usually considered to minimize the impact of Rician noise on the quality of BrainWeb images are matched with the Gaussian filter (GF) and an anisotropic diffusion filter, based on the gradient of the image (GADF). Each of these filters has 2 parameters that control their operation and, therefore, undergo a rigorous tuning process to identify the optimal values that guarantee the best performance of both the GF and the GADF. The peak of the signal-to-noise ratio (PSNR) and the computation time are considered as key elements to analyze the behavior of each of the filtering techniques applied. The results indicate that: a) both filters generate PSNR values comparable to each other. b) The GF requires a significantly shorter computation time to soften the Rician noise present in the considered DB.