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dc.rights.licenseLicencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacionalspa
dc.contributor.authorVera, Miguel
dc.contributor.authorHuérfano, Yoleidy
dc.contributor.authorHernández, Carlos
dc.contributor.authorValbuena, Oscar
dc.contributor.authorSalazar, Williams
dc.contributor.authorVera, María Isabel
dc.contributor.authorBarrera, Doris
dc.contributor.authorBorrero, Maryury
dc.contributor.authorMolina, Ángel Valentín
dc.contributor.authorMartínez, Luis Javier
dc.contributor.authorSalazar, Juan
dc.contributor.authorGelvez, Elkin
dc.contributor.authorContreras, Yudith
dc.contributor.authorSaenz, Frank
dc.description.abstractThis work evaluates the performance of some methods employed for assessing the volume of seven subdural hematomas (EDH), present in multi-layer computed tomography images. Firstly, a reference volume is considered to be that obtained by a neurosurgeon using the manual planimetric method (MPM). Secondly, the volume of the 7 EDHs 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 calculation of the volume of the hematoma under the assumption that the EDH has an ellipsoidal shape. In third place, an intelligent automatic technique (SAT) is implemented that generates the three-dimensional segmentation of each EDH and from it the volume of the hematoma is calculated. The SAT consists of the pre-processing, segmentation and post-processing stages. In order to make judgments about the performance of the SAT, the Dice coefficient (Dc) is used to compare the dilated segmentations of the EDH with the EDH segmentations generated manually. Finally, the percentage relative error is calculated as a metric to evaluate the methodologies considered. The results show that the SAT method exhibits the best performance generating an average percentage error of less than 2%.eng
dc.publisherSociedad Latinoamericana de Hipertensiónspa
dc.sourceRevista Latinoamericana de Hipertensiónspa
dc.sourceVol. 13, No. 4 (2018)spa
dc.subjectABC Methodseng
dc.subjectAutomatic Intelligent Techniqueeng
dc.subjectVolumetry of epidural hematomaseng
dc.titleVolumetry of epidural hematomas in computed tomography images: Comparative study between linear and volumetric methodseng
dc.title.alternativeEstimación del tamaño de hematomas epidurales en imágenes de tomografía computarizada: estudio comparativo entre métodos lineales y volumétricosspa
dcterms.referencesStippler M. Craniocerebral trauma. In: Daroff RB, Jankovic J, Mazziotta JC, Pomeroy SL, eds. Bradley's Neurology in Clinical Practice. 7th ed. Philadelphia, PA: Elsevier; 2016:chap 62.eng
dcterms.referencesMezzadri J., Goland J., y Sokolvsky M. Introducción a la Neurocirugía. Capítulo: Patología vascular II. Ediciones Journal. Segunda edición.
dcterms.referencesVera M. Segmentación de estructuras cardiacas en imágenes de tomografía computarizada multi-corte. Ph.D. dissertation, Universidad de los Andes, Mérida-Venezuela,
dcterms.referencesMaiera A, Wigstrm L, Hofmann H, Hornegger J, Zhu L, Strobel N, Fahrig R. Three-dimensional anisotropic adaptive filtering of projection data for noise reduction in cone beam CT. Medical Physics. 2011;38(11):5896–909.eng
dcterms.referencesKroft L, De Roos A, Geleijns J. Artifacts in ECG–synchronized MDCT coronary angiography. American Journal of Roentgenology. 2007;189(3):581–91.eng
dcterms.referencesVera M., Huérfano Y., Contreras J., Vera M. I., Salazar W., Vargas S., Chacón J. y Rodríguez J. (2017). Segmentación de hematomas epidurales, usando una técnica computacional no lineal en imágenes de tomografía computarizada cerebral. Archivos Venezolanos de Farmacología y Terapéutica Volumen 36(6),
dcterms.referencesHu T., Yan L., Yan Peng., Wang X., Yue G. Assessment of the ABC/2 Method of Epidural Hematoma Volume Measurement as Compared to Computer-Assisted Planimetric Analysis. Biological Research for Nursing. 2016, 18(1) 5-11.eng
dcterms.referencesYan P, Yan L, Hu T, Zhang Z, Feng J, Zhao H. (2016) Assessment of the accuracy of ABC/2 variations in traumatic epidural hematoma volume estimation: a retrospective study. PeerJ 4:e1921https://doi. org/10.7717/peerj.1921eng
dcterms.referencesreeman, W., Barrett, K., Bestic, J.,Meschia, J., Broderick, D., Brott, T. Computer-assisted volumetric analysis comparedwith ABC/2 method for assessing warfarinrelated intracranial hemorrhage volumes. 2008, Neurocritical Care, 9, 307–312.eng
dcterms.referencesLiao C., Xiao F., Wong J., Chiang I. Computer-aided diagnosis of intracranial hematoma with brain deformation on computed tomography. Computerized Medical Imaging and Graphics 34 (2010) 563–571.eng
dcterms.referencesKamnitsas K., Lediga C., Newcombeb V., Simpsonb J., Kaneb A., Menonb D., Rueckerta D., Glockera B. Efficient Multi-Scale 3D CNN with fully connected CRF for Accurate Brain Lesion Segmentation. Medical Image Analysis, Vol 23, pp.1603- 1659, 2017.eng
dcterms.referencesHuttner H., Steiner T., Hartmann M., Köhrmann M., Juettler E., Mueller S, Wikner J., Meyding U., Schramm P., Schwab S. y Schellinger P. (2006). Comparison of ABC/2 Estimation Technique to Computer- Assisted Planimetric Analysis in Warfarin-Related Intracerebral Parenchymal Hemorrhage. Stroke. 2006;37:404-408.eng

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