Automatic segmentation of epidural hematomas using a computational technique based on intelligent operators: a clinical utility
| dc.contributor.author | Salazar, Juan | |
| dc.contributor.author | Vera, Miguel | |
| dc.contributor.author | Huérfano, Yoleidy | |
| dc.contributor.author | Valbuena, Oscar | |
| dc.contributor.author | Salazar, Williams | |
| dc.contributor.author | Vera, María Isabel | |
| dc.contributor.author | Gelvez, Elkin | |
| dc.contributor.author | Contreras, Yudith | |
| dc.contributor.author | Borrero, Maryury | |
| dc.contributor.author | Vivas, Marisela | |
| dc.contributor.author | Barrera, Doris | |
| dc.contributor.author | Hernández, Carlos | |
| dc.contributor.author | Molina, Ángel Valentín | |
| dc.contributor.author | Martínez, Luis Javier | |
| dc.contributor.author | Sáenz, Frank | |
| dc.date.accessioned | 2019-01-25T14:15:54Z | |
| dc.date.available | 2019-01-25T14:15:54Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | This 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. | eng |
| dc.description.abstract | Este artículo propone una técnica computacional no lineal para la segmentación de los hematomas epidurales (EDH), presente en 7 bases de datos de imágenes cerebrales de tomografía multicapa. Esta técnica consta de 3 etapas desarrolladas en el dominio tridimensional, a saber: preprocesamiento, segmentación y cuantificación del volumen ocupado por cada uno de los EDH segmentados. Para hacer juicios de valor sobre el rendimiento de la técnica propuesta, las segmentaciones dilatadas de EDH, obtenidas automáticamente, y las segmentaciones de EDH, generadas manualmente por un neurocirujano, se comparan utilizando el coeficiente de Dice (Dc). La combinación de parámetros vinculados al valor más alto de Dc define los parámetros óptimos de cada uno de los algoritmos computacionales que conforman la técnica no lineal propuesta. Los resultados obtenidos permiten el reporte de un Dc superior a 0.90 que indica una buena correlación entre las segmentaciones manuales y las producidas por la técnica computacional desarrollada. Finalmente, como aplicación clínica inmediata, considerando las segmentaciones automáticas, el volumen de cada hematoma se calcula considerando tanto el tamaño del vóxel de cada base de datos como el número de vóxeles que conforman los hematomas segmentados. | spa |
| dc.identifier.issn | 26107988 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.12442/2522 | |
| dc.language.iso | eng | eng |
| dc.publisher | Sociedad Venezolana de Farmacología Clínica y Terapéutica | spa |
| dc.rights.accessrights | info:eu-repo/semantics/openAccess | |
| dc.rights.license | Licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional | spa |
| dc.source | Revista AVFT-Archivos Venezolanos de Farmacología y Terapéutica | spa |
| dc.source | Vol. 37, No. 4 (2018) | spa |
| dc.source.uri | http://www.revistaavft.com/images/revistas/2018/avft_4_2018/2_automatic_segmentation_of_epidural.pdf | eng |
| dc.subject | Brain Tomography | eng |
| dc.subject | Epidural Hematomas | eng |
| dc.subject | Nonlinear Computational Technique | eng |
| dc.subject | Smart Operators | eng |
| dc.subject | Segmentation | eng |
| dc.subject | Tomografía cerebral | spa |
| dc.subject | Hematomas epidurales | spa |
| dc.subject | Técnica computacional no lineal | spa |
| dc.subject | Operadores inteligentes | spa |
| dc.subject | Segmentación | spa |
| dc.title | Automatic segmentation of epidural hematomas using a computational technique based on intelligent operators: a clinical utility | eng |
| dc.title.alternative | Segmentación automática de hematomas epidurales usando una técnica computacional, basada en operadores inteligentes: utilidad clínica | spa |
| dc.type | article | eng |
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