Realce por similaridad local para la segmentación automática de la arteria aorta torácica en imágenes de tomografía computarizada cardiaca.
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| Title: | Realce por similaridad local para la segmentación automática de la arteria aorta torácica en imágenes de tomografía computarizada cardiaca. |
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| Alternate Title: | Enhancement by local similarity for automatic segmentation of the thoracic aorta in cardiac computed tomography. |
| Authors: | Contreras-Velásquez, Julio1 j.contrerasv@unisimonbolivar.edu.co, Vera, Miguel1,2, Huérfano, Yoleidy2, Del Mar, Atilio3 atiliodelmar@yahoo.com, Wilches-Durán, Sandra2, Graterol-Rivas, Modesto2, Riaño-Wilches, Daniela4, Rojas, Joselyn5, Bermúdez, Valmore2,6 |
| Source: | Revista Latinoamericana de Hipertensión. 2017, Vol. 12 Issue 3, p88-94. 7p. |
| Abstract (English): | This work proposes a strategy to segment the thoracic aortic artery (TAA) into three-dimensional (3-D) multi-layer computed tomography images. This strategy consists of the stages of filtering, segmentation and intonation of parameters. The filtering stage employs a technique called local similarity enhancement (LSE) in order to reduce the impact of the artifacts and attenuate noise in the quality of the images. This technique combines an averaging filter, an edge detector filter (called black top hat) and a Gaussian filter (GF). On the other hand, a clustering algorithm, called region growth (RG), is implemented during the 3-D segmentation stage, which is applied to the pre-processed images. During the intonation of parameters of the proposed strategy, the Dice coefficient (Dc) is used to compare the segmentations, of the TAA, obtained automatically, with the segmentation of the TAA generated, manually, by a cardiologist. The combination of parameters that generated the highest Dc considering the instant of diastole is then applied to the 9 remaining three-dimensional images, obtaining an average Dc higher than 0.92 which indicates a good correlation between the segmentations generated by the expert cardiologist and those produced by The strategy developed. [ABSTRACT FROM AUTHOR] |
| Abstract (Spanish): | Mediante este trabajo se propone una estrategia para segmentar la arteria aórtica torácica (TAA) en imágenes tridimensionales (3-D) de tomografía computarizada multicapa. Esta estrategia consta de las etapas de filtrado, segmentación y entonación de parámetros. La etapa de filtrado, se emplea una técnica denominada realce por similaridad local (LSE) con el propósito de disminuir el impacto de los artefactos y atenuar el ruido en la calidad de las imágenes. Esta técnica, combina un filtro promediador, un filtro detector de bordes (denominado black top hat) y un filtro gaussiano (GF). Por otra parte, durante la etapa de segmentación 3-D se implementa un algoritmo de agrupamiento, denominado crecimiento de regiones (RG), el cual es aplicado a las imágenes pre-procesadas. Durante la entonación de parámetros de la estrategia propuesta, el coeficiente de Dice (Dc) es utilizado para comparar las segmentaciones, de la TAA, obtenidas automáticamente, con la segmentación de la TAA generada, manualmente, por un cardiólogo. La combinación de parámetros que generó el Dc más elevado considerando el instante de diástole se aplica luego a las 9 imágenes tridimensionales restantes, obteniéndose un Dc promedio superior a 0.92 lo cual indica una buena correlación entre las segmentaciones generadas por el experto cardiólogo y las producidas por la estrategia desarrollada. [ABSTRACT FROM AUTHOR] |
| Copyright of Revista Latinoamericana de Hipertensión is the property of Revista Latinoamericana de Hipertension 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 DbLabel: MedicLatina An: 123526868 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Realce por similaridad local para la segmentación automática de la arteria aorta torácica en imágenes de tomografía computarizada cardiaca. – Name: TitleAlt Label: Alternate Title Group: TiAlt Data: Enhancement by local similarity for automatic segmentation of the thoracic aorta in cardiac computed tomography. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Contreras-Velásquez%2C+Julio%22">Contreras-Velásquez, Julio</searchLink><relatesTo>1</relatesTo><i> j.contrerasv@unisimonbolivar.edu.co</i><br /><searchLink fieldCode="AR" term="%22Vera%2C+Miguel%22">Vera, Miguel</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AR" term="%22Huérfano%2C+Yoleidy%22">Huérfano, Yoleidy</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Del+Mar%2C+Atilio%22">Del Mar, Atilio</searchLink><relatesTo>3</relatesTo><i> atiliodelmar@yahoo.com</i><br /><searchLink fieldCode="AR" term="%22Wilches-Durán%2C+Sandra%22">Wilches-Durán, Sandra</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Graterol-Rivas%2C+Modesto%22">Graterol-Rivas, Modesto</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Riaño-Wilches%2C+Daniela%22">Riaño-Wilches, Daniela</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Rojas%2C+Joselyn%22">Rojas, Joselyn</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Bermúdez%2C+Valmore%22">Bermúdez, Valmore</searchLink><relatesTo>2,6</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Revista+Latinoamericana+de+Hipertensión%22">Revista Latinoamericana de Hipertensión</searchLink>. 2017, Vol. 12 Issue 3, p88-94. 7p. – Name: Abstract Label: Abstract (English) Group: Ab Data: This work proposes a strategy to segment the thoracic aortic artery (TAA) into three-dimensional (3-D) multi-layer computed tomography images. This strategy consists of the stages of filtering, segmentation and intonation of parameters. The filtering stage employs a technique called local similarity enhancement (LSE) in order to reduce the impact of the artifacts and attenuate noise in the quality of the images. This technique combines an averaging filter, an edge detector filter (called black top hat) and a Gaussian filter (GF). On the other hand, a clustering algorithm, called region growth (RG), is implemented during the 3-D segmentation stage, which is applied to the pre-processed images. During the intonation of parameters of the proposed strategy, the Dice coefficient (Dc) is used to compare the segmentations, of the TAA, obtained automatically, with the segmentation of the TAA generated, manually, by a cardiologist. The combination of parameters that generated the highest Dc considering the instant of diastole is then applied to the 9 remaining three-dimensional images, obtaining an average Dc higher than 0.92 which indicates a good correlation between the segmentations generated by the expert cardiologist and those produced by The strategy developed. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Abstract (Spanish) Group: Ab Data: Mediante este trabajo se propone una estrategia para segmentar la arteria aórtica torácica (TAA) en imágenes tridimensionales (3-D) de tomografía computarizada multicapa. Esta estrategia consta de las etapas de filtrado, segmentación y entonación de parámetros. La etapa de filtrado, se emplea una técnica denominada realce por similaridad local (LSE) con el propósito de disminuir el impacto de los artefactos y atenuar el ruido en la calidad de las imágenes. Esta técnica, combina un filtro promediador, un filtro detector de bordes (denominado black top hat) y un filtro gaussiano (GF). Por otra parte, durante la etapa de segmentación 3-D se implementa un algoritmo de agrupamiento, denominado crecimiento de regiones (RG), el cual es aplicado a las imágenes pre-procesadas. Durante la entonación de parámetros de la estrategia propuesta, el coeficiente de Dice (Dc) es utilizado para comparar las segmentaciones, de la TAA, obtenidas automáticamente, con la segmentación de la TAA generada, manualmente, por un cardiólogo. La combinación de parámetros que generó el Dc más elevado considerando el instante de diástole se aplica luego a las 9 imágenes tridimensionales restantes, obteniéndose un Dc promedio superior a 0.92 lo cual indica una buena correlación entre las segmentaciones generadas por el experto cardiólogo y las producidas por la estrategia desarrollada. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Revista Latinoamericana de Hipertensión is the property of Revista Latinoamericana de Hipertension 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.) |
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| RecordInfo | BibRecord: BibEntity: Languages: – Code: spa Text: Spanish PhysicalDescription: Pagination: PageCount: 7 StartPage: 88 Titles: – TitleFull: Realce por similaridad local para la segmentación automática de la arteria aorta torácica en imágenes de tomografía computarizada cardiaca. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Contreras-Velásquez, Julio – PersonEntity: Name: NameFull: Vera, Miguel – PersonEntity: Name: NameFull: Huérfano, Yoleidy – PersonEntity: Name: NameFull: Del Mar, Atilio – PersonEntity: Name: NameFull: Wilches-Durán, Sandra – PersonEntity: Name: NameFull: Graterol-Rivas, Modesto – PersonEntity: Name: NameFull: Riaño-Wilches, Daniela – PersonEntity: Name: NameFull: Rojas, Joselyn – PersonEntity: Name: NameFull: Bermúdez, Valmore IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: 2017 Type: published Y: 2017 Identifiers: – Type: issn-print Value: 18564550 Numbering: – Type: volume Value: 12 – Type: issue Value: 3 Titles: – TitleFull: Revista Latinoamericana de Hipertensión Type: main |
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