Automatic segmentation of epidural hematomas using a computational technique based on intelligent operators: a clinical utility

• Published in: Archivos venezolanos de farmacología y terapéutica 2018-01, Vol.37 (4), p.320-325
• Main Authors: 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, Frank
• Format: Article
• Language: English
• Subjects: Brain; Hemophilia; Medical imaging; Tomography
• ISSN: 0798-0264; 2610-7988

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 İ 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.