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

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Title: Automatic segmentation of epidural hematomas using a computational technique based on intelligent operators: a clinical utility.
Alternate Title: Segmentación automática de hematomas epidurales usando una técnica computacional, basada en operadores inteligentes: utilidad clínica.
Authors: Salazar, Juan1, Vera, Miguel1,2 m.avera@unisimonbolivar.edu.co, Huérfano, Yoleidy2, Valbuena, Oscar3, Salazar, Williams4, Vera, María Isabel4, Gelvez, Elkin1, Contreras, Yudith1, Borrero, Maryury1, Vivas, Marisela5, Barrera, Doris1, Hernández, Carlos1, Molina, Ángel Valentín6, Martínez, Luis Javier7, Sáenz, Frank1
Source: Archivos Venezolanos de Farmacología y Terapéutica. 10/1/2018, Vol. 37 Issue 4, p320-325. 6p.
Subjects: EPIDURAL hematoma, COMPUTED tomography, BRAIN imaging, NEUROSURGEONS, IMAGE segmentation
Abstract (English): 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. [ABSTRACT FROM AUTHOR]
Abstract (Spanish): 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. [ABSTRACT FROM AUTHOR]
Copyright of Archivos Venezolanos de Farmacología y Terapéutica is the property of Archivos Venezolanos de Farmacologia y Terapeutica and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: MedicLatina
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Header DbId: lth
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PubType: Academic Journal
PubTypeId: academicJournal
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Items – Name: Title
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  Group: Ti
  Data: Automatic segmentation of epidural hematomas using a computational technique based on intelligent operators: a clinical utility.
– Name: TitleAlt
  Label: Alternate Title
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  Data: Segmentación automática de hematomas epidurales usando una técnica computacional, basada en operadores inteligentes: utilidad clínica.
– Name: Author
  Label: Authors
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  Data: <searchLink fieldCode="AR" term="%22Salazar%2C+Juan%22">Salazar, Juan</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Vera%2C+Miguel%22">Vera, Miguel</searchLink><relatesTo>1,2</relatesTo><i> m.avera@unisimonbolivar.edu.co</i><br /><searchLink fieldCode="AR" term="%22Huérfano%2C+Yoleidy%22">Huérfano, Yoleidy</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Valbuena%2C+Oscar%22">Valbuena, Oscar</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Salazar%2C+Williams%22">Salazar, Williams</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Vera%2C+María+Isabel%22">Vera, María Isabel</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Gelvez%2C+Elkin%22">Gelvez, Elkin</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Contreras%2C+Yudith%22">Contreras, Yudith</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Borrero%2C+Maryury%22">Borrero, Maryury</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Vivas%2C+Marisela%22">Vivas, Marisela</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Barrera%2C+Doris%22">Barrera, Doris</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Hernández%2C+Carlos%22">Hernández, Carlos</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Molina%2C+Ángel+Valentín%22">Molina, Ángel Valentín</searchLink><relatesTo>6</relatesTo><br /><searchLink fieldCode="AR" term="%22Martínez%2C+Luis+Javier%22">Martínez, Luis Javier</searchLink><relatesTo>7</relatesTo><br /><searchLink fieldCode="AR" term="%22Sáenz%2C+Frank%22">Sáenz, Frank</searchLink><relatesTo>1</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Archivos+Venezolanos+de+Farmacología+y+Terapéutica%22">Archivos Venezolanos de Farmacología y Terapéutica</searchLink>. 10/1/2018, Vol. 37 Issue 4, p320-325. 6p.
– Name: Subject
  Label: Subjects
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  Data: <searchLink fieldCode="DE" term="%22EPIDURAL+hematoma%22">EPIDURAL hematoma</searchLink><br /><searchLink fieldCode="DE" term="%22COMPUTED+tomography%22">COMPUTED tomography</searchLink><br /><searchLink fieldCode="DE" term="%22BRAIN+imaging%22">BRAIN imaging</searchLink><br /><searchLink fieldCode="DE" term="%22NEUROSURGEONS%22">NEUROSURGEONS</searchLink><br /><searchLink fieldCode="DE" term="%22IMAGE+segmentation%22">IMAGE segmentation</searchLink>
– Name: Abstract
  Label: Abstract (English)
  Group: Ab
  Data: 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. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label: Abstract (Spanish)
  Group: Ab
  Data: 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. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Archivos Venezolanos de Farmacología y Terapéutica is the property of Archivos Venezolanos de Farmacologia y Terapeutica and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=lth&AN=133820296
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      – Code: eng
        Text: English
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        PageCount: 6
        StartPage: 320
    Subjects:
      – SubjectFull: EPIDURAL hematoma
        Type: general
      – SubjectFull: COMPUTED tomography
        Type: general
      – SubjectFull: BRAIN imaging
        Type: general
      – SubjectFull: NEUROSURGEONS
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      – SubjectFull: IMAGE segmentation
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      – TitleFull: Automatic segmentation of epidural hematomas using a computational technique based on intelligent operators: a clinical utility.
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              Text: 10/1/2018
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