Decanato de Investigación

This paper reports on an automatic method for ventricular cavity segmentation in angiographic images. The first step of the method consists in applying a linear regression model that exploits the functional relationship between the original input image and a smoothed version. This intermediate result is used as input to a clustering algorithm, which is based on a region growing technique. The clustering algorithm is a two stage process. In the first stage an initial segmentation is achieved using as input the result of the linear regression and the smoothed version of the input image. The second stage is intended for refining the initial segmentation based on feature vectors including the area, the gray-level average and the centroid of each candidate region. The segmentation method is conceptually simple and provides an accurate contour detection for the left ventricle cavity.

The aim of this research is proposing a 3-D similarity enhancement technique useful for improving the segmentation of cardiac structures in Multi-Slice Computerized Tomography (MSCT) volumes. The similarity enhancement is obtained by subtracting the intensity of the current voxel and the gray levels of their adjacent voxels in two volumes resulting after preprocessing. Such volumes are: a. - a volume obtained after applying a Gaussian distribution and a morphological top-hat filter to the input and b. - a smoothed volume generated by processing the input with an average filter. Then, the similarity volume is used as input to a region growing algorithm. This algorithm is applied to extract the shape of cardiac structures, such as left and right ventricles, in MSCT volumes. Qualitative and quantitative results show the good performance of the proposed approach for discrimination of cardiac cavities.

Background: The multi–slice computerized tomography (MSCT) is a medical imaging modality that has been used to determine the size and location of the stomach cancer. Additionally, MSCT is considered the best modality for the staging of gastric cancer. One way to assess the type 2 cancer of stomach is by detecting the pathological structure with an image segmentation approach. The tumor segmentation of MSCT gastric cancer images enables the diagnosis of the disease condition, for a given patient, without using an invasive method as surgical intervention. Methods: This approach consists of three stages. The initial stage, an image enhancement, consists of a method for correcting non homogeneities present in the background of MSCT images. Then, a segmentation stage using a clustering method allows to obtain the adenocarcinoma morphology. In the third stage, the pathology region is reconstructed and then visualized with a three–dimensional (3–D) computer graphics procedure based on marc...

In this research, an approach to assess the heart dynamics is reported. The cardiac magnetic resonance images are considered for assessing the left ventricle motion and deformation. The shape of the cavity is obtained by means a segmentation procedure based on a clustering algorithm at an initial instant. This three-dimensional structure is used to establish a region of interest around the border of the structure. An optical flow method allows determining the displacement vector of this region and then defining the shapes of the cavity during the all cardiac cycle. The points of the left ventricle are followed using the displacement vectors in the cardiac cycle, obtaining thus, a dense motion field of the cavity. This approximate deformation field is refined with a correspondence method that working in the three-dimensional space. The mapping of the points that define the left ventricle in the cardiac cycle obtained with the correspondence procedure are then used for computing a set...

The X-ray angiography images are routinely used to assess the blood vessels. The acquisition procedure considers a medical imaging system which allows obtaining views of the vessel while the blood flows thought them. The X-ray source is influenced on the region to be viewed and then, the projection of the all anatomical structures in the champ of view is shown through an image intensifier. The information of the blood vessel is impacted for the other structures. Additionally, the blood and the contrast product required in the acquisition are not mixed homogeneously, producing artifacts in the images. Finally, the noise is also an impact factor in the quality of the angiography images. In the coronary vessel case, the branches of the network are superposed. In this paper, an enhancement procedure to diminish the uncertainty associated to X-ray angiography images is reported. The relation between two versions of the angiograms is determined using a fuzzy connector considering that thi...

Antonio J. Bravo, MgSc, PhD1*, Felida Roa, MgSc2, Miguel Vera, MgSc, PhD3,4, Julio Contreras-Velásquez, MgSc4, Yoleidy Huérfano, MgSc3, José Chacón, MgSc, PhD4, Sandra Wilches-Durán, MgSc4, Modesto Graterol-Rivas, MgSc, PhD4, Daniela Riaño-Wilches, BSc5, Joselyn Rojas, MD, MSc6, Valmore Bermúdez, MD, MSc, MPH, PhD4,7 1Coordinación de Investigación Industrial, Decanato de Investigación, Universidad Nacional Experimental del Táchira, San Cristóbal, 5001, Táchira, Venezuela. E-mail de correspondencia: abravo@unet.edu.ve* 2Grupo de Bioingeniería, Decanato de Investigación, Universidad Nacional Experimental del Táchira, San Cristóbal, 5001, Táchira, Venezuela 3Grupo de Investigación en Procesamiento Computacional de Datos (GIPCD-ULA) Universidad de Los Andes-Táchira, Venezuela 4Grupo de Investigación Altos Estudios de Frontera (ALEF), Universidad Simón Bolívar, Cúcuta, Colombia 5Facultad de Medicina, Universidad de los Andes, Bogotá, Colombia. 6Pulmonary and Critical Care Medicine Depart...

El analisis de imagenes cardiovasculares constituye una herramienta util para el diagnostico, tratamiento y monitoreo de enfermedades cardiovasculares. Las tecnicas de procesamiento de imagenes permiten la evaluacion cuantitativa no-invasiva de la funcion cardiaca, proporcionando informacion morfologica, funcional y dinamica. Los progresos tecnologicos recientes en ultrasonido han permitido incrementar la calidad del tratamiento al paciente, gracias al uso de tecnicas modernas de procesamiento y analisis de las imagenes. Sin embargo, la adquisicion de estas imagenes tridimensionales (3D) dinamicas conduce a la produccion de grandes volumenes de datos para procesar, a partir de los cuales las estructuras cardiacas deben ser extraidas y analizadas durante el ciclo cardiaco. Herramientas de extraccion, de visualizacion tridimensional, y de cuantificacion son usadas actualmente dentro de la rutina clinica, pero desafortunadamente necesitan de una interaccion importante con el medico. Es...

El analisis de imagenes constituye una herramienta util para el diagnostico, tratamiento y monitoreo de diversas enfermedades. Las tecnicas de procesamiento de imagenes permiten la evaluacion cuantitativa no–invasiva de la fisiopatologia humana, proporcionando informacion morfologica, funcional y dinamica de diferentes estructuras anatomicas. Los progresos tecnologicos recientes sobre las diferentes modalidades de observacion han permitido incrementar la calidad del tratamiento al paciente, gracias al uso de tecnicas modernas de procesamiento de imagenes tridimensionales. Sin embargo, la adquisicion de estas imagenes tridimensionales dinamicas conduce a la produccion de grandes volumenes de datos para procesar, a partir de los cuales, las estructuras anatomicas deben ser extraidas y analizadas, respetando las restricciones impuestas por el contexto clinico. Herramientas de extraccion, de visualizacion tridimensional y de cuantificacion son usadas actualmente dentro de la rutina clin...