Examinando por Autor "Pardo, Aldo"
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Ítem Computational assessment of stomach tumor volume from multi-slice computerized tomography images in presence of type 2 cancer [version 2; referees: 1 approved, 1 not approved](F1000 Research Ltda., 2018-07) Chacón, Gerardo; Rodríguez, Johel E.; Bermúdez, Valmore; Vera, Miguel; Hernández, Juan Diego; Vargas, Sandra; Pardo, Aldo; Lameda, Carlos; Madriz, Delia; Bravo, Antonio J.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 marching cubes algorithm. In order to validate the segmentations, the Dice score is used as a metric function useful for comparing the segmentations obtained using the proposed method with respect to ground truth volumes traced by a clinician. Results: A total of 8 datasets available for patients diagnosed, from the cancer data collection of the project, Cancer Genome Atlas Stomach Adenocarcinoma (TCGASTAD) is considered in this research. The volume of the type 2 stomach tumor is estimated from the 3–D shape computationally segmented from the each dataset. These 3–D shapes are computationally reconstructed and then used to assess the morphopathology macroscopic features of this cancer. Conclusions: The segmentations obtained are useful for assessing qualitatively and quantitatively the stomach type 2 cancer. In addition, this type of segmentation allows the development of computational models that allow the planning of virtual surgical processes related to type 2 cancer.Ítem A score function as quality measure for cardiac image enhancement techniques assessment(Sociedad Latinoamericana de Hipertensión, 2019) Chacón, Gerardo; Rodríguez, Johel E.; Bermúdez, Valmore; Flórez, Anderson; Del Mar, Atilio; Pardo, Aldo; Lameda, Carlos; Madriz, Delia; Bravo, Antonio J.A score function useful as a quantitative measure of the performance of the medical image enhancement techniques is reported in this paper. The measure proposed is based on merging of full–reference and blind–reference image enhancement measures. The score function is the average of the weighted sum of the image enhancement measures normalized between zero and one. The novel measure is validated considering as a hypothesis that values maximizing score function have that maximize the values of the metrics (Dice coefficient) used to evaluate certain previously reported cardiac image segmentation approach. The values of score function and Dice score reached the maximum value for the same cardiac volumes segmented.Ítem Simultaneous evaluation of volumes and synergistic motion of the left ventricle from X-ray angiograms using a unified computational framework(Cooperativa servicios y suministros 212518 RS, 2019) Chacón, Gerardo; Rodríguez, Johel E.; Bermúdez, Valmore; Flórez, Anderson; Del Mar, Atilio; Pardo, Aldo; Lameda, CarlosX-rays angiograms of the left ventricle as the main cavity of the human heart are acquired at the catheterization rooms routinely in order to evaluate the cardiac dynamic function. The global measurement of volumes, ejection fraction and synergistic motion associated with the ventricular cavity are considered in the assessment of such function. A precise left ventricle silhouette on the angiograms is necessary to calculate the function descriptors. A segmentation method is required to obtain the projected cavity shape