Assessment of methods for volumetric quantification of intracerebral hematomas in computerized tomography images

This work evaluates the performance of computational methods aimed at volume generation of five intracerebral hematomas (ICH), present in multi-layer computed tomography images, by means of three complementary steps. First. A ground truth volume or reference volume (RV) is considered. This RV is obt...

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Autores:
Vera, Miguel
Huérfano, Yoleidy
Barrera, Doris
Valbuena, Oscar
Salazar, Williams
Vera, María Isabel
Hernández, Carlos
Vivas, Marisela
Borrero, Maryury
Molina, Ángel Valentín
Martínez, Luis Javier
Salazar, Juan
Gelvez, Elkin
Contreras, Yudith
Sáenz, Frank
Tipo de recurso:
Fecha de publicación:
2018
Institución:
Universidad Simón Bolívar
Repositorio:
Repositorio Digital USB
Idioma:
spa
OAI Identifier:
oai:bonga.unisimon.edu.co:20.500.12442/2520
Acceso en línea:
http://hdl.handle.net/20.500.12442/2520
Palabra clave:
ABC Methods
Intelligent Automatic Technique
Segmentation
Intracerebral Hematoma Volumetry
Métodos ABC
Técnica automática inteligente
Segmentación
Volumetría de hematomas intracerebrales
Rights
License
Licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional
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dc.title.eng.fl_str_mv Assessment of methods for volumetric quantification of intracerebral hematomas in computerized tomography images
dc.title.alternative.spa.fl_str_mv Evaluación de métodos para la cuantificación volumétrica de hematomas intracerebrales en imágenes de tomografía computarizada
title Assessment of methods for volumetric quantification of intracerebral hematomas in computerized tomography images
spellingShingle Assessment of methods for volumetric quantification of intracerebral hematomas in computerized tomography images
ABC Methods
Intelligent Automatic Technique
Segmentation
Intracerebral Hematoma Volumetry
Métodos ABC
Técnica automática inteligente
Segmentación
Volumetría de hematomas intracerebrales
title_short Assessment of methods for volumetric quantification of intracerebral hematomas in computerized tomography images
title_full Assessment of methods for volumetric quantification of intracerebral hematomas in computerized tomography images
title_fullStr Assessment of methods for volumetric quantification of intracerebral hematomas in computerized tomography images
title_full_unstemmed Assessment of methods for volumetric quantification of intracerebral hematomas in computerized tomography images
title_sort Assessment of methods for volumetric quantification of intracerebral hematomas in computerized tomography images
dc.creator.fl_str_mv Vera, Miguel
Huérfano, Yoleidy
Barrera, Doris
Valbuena, Oscar
Salazar, Williams
Vera, María Isabel
Hernández, Carlos
Vivas, Marisela
Borrero, Maryury
Molina, Ángel Valentín
Martínez, Luis Javier
Salazar, Juan
Gelvez, Elkin
Contreras, Yudith
Sáenz, Frank
dc.contributor.author.none.fl_str_mv Vera, Miguel
Huérfano, Yoleidy
Barrera, Doris
Valbuena, Oscar
Salazar, Williams
Vera, María Isabel
Hernández, Carlos
Vivas, Marisela
Borrero, Maryury
Molina, Ángel Valentín
Martínez, Luis Javier
Salazar, Juan
Gelvez, Elkin
Contreras, Yudith
Sáenz, Frank
dc.subject.eng.fl_str_mv ABC Methods
Intelligent Automatic Technique
Segmentation
Intracerebral Hematoma Volumetry
topic ABC Methods
Intelligent Automatic Technique
Segmentation
Intracerebral Hematoma Volumetry
Métodos ABC
Técnica automática inteligente
Segmentación
Volumetría de hematomas intracerebrales
dc.subject.spa.fl_str_mv Métodos ABC
Técnica automática inteligente
Segmentación
Volumetría de hematomas intracerebrales
description This work evaluates the performance of computational methods aimed at volume generation of five intracerebral hematomas (ICH), present in multi-layer computed tomography images, by means of three complementary steps. First. A ground truth volume or reference volume (RV) is considered. This RV is obtained, by a neurosurgeon, using the manual planimetric method (MPM). In a second step, the volumetry of the 5 ICH’s 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 calculating hematoma volume under the geometric assumption that the ICH has an ellipsoidal shape. In a third step, a smart automatic technique (SAT) is implemented to generate the three-dimensional segmentation of each ICH. In the context of the present work, the expression SAT method is used to refer to the new methodology proposed to calculate the volume of the ICH. In order to evaluate the performance of the SAT, the Dice coefficient (Dc) is used to compare the dilated segmentations of the ICH with the ICH segmentations generated, manually, by a neurosurgeon. Finally, the percentage relative error is calculated as a measure to evaluate the methodologies considered. The results show that the SAT method exhibits the best performance, generating an average percentage error of less than 3%.
publishDate 2018
dc.date.issued.none.fl_str_mv 2018
dc.date.accessioned.none.fl_str_mv 2019-01-24T22:26:20Z
dc.date.available.none.fl_str_mv 2019-01-24T22:26:20Z
dc.type.eng.fl_str_mv article
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.identifier.issn.none.fl_str_mv 26107988
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/20.500.12442/2520
identifier_str_mv 26107988
url http://hdl.handle.net/20.500.12442/2520
dc.language.iso.eng.fl_str_mv spa
language spa
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.license.spa.fl_str_mv Licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional
rights_invalid_str_mv Licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacional
http://purl.org/coar/access_right/c_abf2
dc.publisher.spa.fl_str_mv Sociedad Venezolana de Farmacología Clínica y Terapéutica
dc.source.spa.fl_str_mv Revista AVFT-Archivos Venezolanos de Farmacología y Terapéutica
Vol. 37, No. 4 (2018)
institution Universidad Simón Bolívar
dc.source.uri.eng.fl_str_mv http://www.revistaavft.com/images/revistas/2018/avft_4_2018/4_assessmentof_methods.pdf
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spelling Licencia de Creative Commons Reconocimiento-NoComercial-CompartirIgual 4.0 Internacionalhttp://purl.org/coar/access_right/c_abf2Vera, Miguelc485e4e3-5bbd-4d00-8ec7-e5bc8a0a21e3Huérfano, Yoleidy769899ba-e6a1-4144-95c2-ff4614f93578Barrera, Doris4b365c16-7d6f-4aee-985c-e70d635e8807Valbuena, Oscar262b3f8e-b422-4786-b036-2aaa5b963f84Salazar, Williamsfd007214-08c4-4cd6-ae19-7f2ba4f184eaVera, María Isabelc522f56e-ec03-4aa6-9e83-d339a37388acHernández, Carlosa82d5fb1-0724-456f-8223-93882ad7278dVivas, Mariselafce67a67-3a3b-493c-8fed-422fb00a2e71Borrero, Maryuryce8424b3-6f43-4a46-8f73-214fafbb62fdMolina, Ángel Valentín5fcd607f-8710-40a9-b4dc-b9d1f71d1c1eMartínez, Luis Javierd0fa0a36-7752-496a-979e-48fdb02a5ee9Salazar, Juanfbd053e7-5aea-424c-812f-92153ecb9181Gelvez, Elkin90dd023c-1cb7-48ef-bff5-4071ee82a94cContreras, Yudith5ec79ce9-bc7e-44bb-95cb-bf1dab3e3a64Sáenz, Frank5a93b50c-3ebe-476e-8aa6-4286185e2b1d2019-01-24T22:26:20Z2019-01-24T22:26:20Z201826107988http://hdl.handle.net/20.500.12442/2520This work evaluates the performance of computational methods aimed at volume generation of five intracerebral hematomas (ICH), present in multi-layer computed tomography images, by means of three complementary steps. First. A ground truth volume or reference volume (RV) is considered. This RV is obtained, by a neurosurgeon, using the manual planimetric method (MPM). In a second step, the volumetry of the 5 ICH’s 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 calculating hematoma volume under the geometric assumption that the ICH has an ellipsoidal shape. In a third step, a smart automatic technique (SAT) is implemented to generate the three-dimensional segmentation of each ICH. In the context of the present work, the expression SAT method is used to refer to the new methodology proposed to calculate the volume of the ICH. In order to evaluate the performance of the SAT, the Dice coefficient (Dc) is used to compare the dilated segmentations of the ICH with the ICH segmentations generated, manually, by a neurosurgeon. Finally, the percentage relative error is calculated as a measure to evaluate the methodologies considered. The results show that the SAT method exhibits the best performance, generating an average percentage error of less than 3%.Este trabajo evalúa el rendimiento de los métodos computacionales dirigidos a la generación de volumen de cinco hematomas intracerebrales (HIC), presentes en imágenes de tomografía computarizada de múltiples capas, por medio de tres pasos complementarios. Primero. Se considera un volumen básico o volumen de referencia (RV). Este RV es obtenido, por un neurocirujano, usando el método planimétrico manual (MPM). En un segundo paso, la volumetría de los 5 ICH se obtiene considerando tanto la versión original del método ABC / 2 como dos de sus variantes, identificadas en este trabajo como el método ABC / 3 y el método 2ABC / 3. Los métodos ABC permiten calcular el volumen del hematoma bajo la suposición geométrica de que el ICH tiene una forma elipsoidal. En un tercer paso, se implementa una técnica automática inteligente (SAT) para generar la segmentación tridimensional de cada ICH. En el contexto del presente trabajo, la expresión método SAT se utiliza para referirse a la nueva metodología propuesta para calcular el volumen del ICH. Para evaluar el rendimiento del SAT, el coeficiente de Dice (Dc) se usa para comparar las segmentaciones dilatadas de la ICH con las segmentaciones ICH generadas, manualmente, por un neurocirujano. Finalmente, el error relativo porcentual se calcula como una medida para evaluar las metodologías consideradas. Los resultados muestran que el método SAT muestra el mejor rendimiento, generando un porcentaje de error promedio de menos del 3%.spaSociedad Venezolana de Farmacología Clínica y TerapéuticaRevista AVFT-Archivos Venezolanos de Farmacología y TerapéuticaVol. 37, No. 4 (2018)http://www.revistaavft.com/images/revistas/2018/avft_4_2018/4_assessmentof_methods.pdfABC MethodsIntelligent Automatic TechniqueSegmentationIntracerebral Hematoma VolumetryMétodos ABCTécnica automática inteligenteSegmentaciónVolumetría de hematomas intracerebralesAssessment of methods for volumetric quantification of intracerebral hematomas in computerized tomography imagesEvaluación de métodos para la cuantificación volumétrica de hematomas intracerebrales en imágenes de tomografía computarizadaarticlehttp://purl.org/coar/resource_type/c_6501Stippler 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.Maiera 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.Kroft L, De Roos A, Geleijns J. Artifacts in ECG–synchronized MDCT coronary angiography. American Journal of Roentgenology. 2007;189(3):581–91.LoPresti M., Bruce S., Camacho E., Kunchala S., Dubois B., Bruce E., Appelboom G., Connolly E. (2014). Hematoma volume as the major determinant of outcomes after intracerebral hemorrhage. J Neurol Sci. 2014 Oct 15;345(1-2):3-7.Yildiz O., Arsava E., Akpinar E. y Topcuoglu M. Hematoma volume as a sole predictor of in-hospital mortality following spontaneous Intracerebral. Journal of Turkish Cerebrovascular Diseases 2011 17:2; 63-66.Hu 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.Rodriguez D., Boyko M., Subramaniam S., Klourfeld E., Jo P., Diederichs B., Kosior J., Dowlatshahi D., Aviv R., Molina C., Hill M. y Demchuk A. Magnitude of Hematoma Volume Measurement Error in Intracerebral Hemorrhage. Stroke. 2016;47:1124-1126.Freeman, W., Barrett, K., Bestic, J.,Meschia, J., Broderick, D., Brott, T. Computer-assisted volumetric analysis compared with ABC/2 method for assessing warfarinrelated intracranial hemorrhage volumes. 2008, Neurocritical Care, 9, 307–312.Kamnitsas 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.Prakash K., Zhou S., Morgan T., Hanley D., Nowinski W. Segmentation and quantification of intra-ventricular/cerebral hemorrhage in CT scans by modified distance regularized level set evolution technique. Int J Comput Assist Radiol Surg. 2012; 7(5): 785-798.Huttner 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.Mezzadri J., Goland J., y Sokolvsky M. Introducción a la Neurocirugía. Capítulo: Patología vascular II. Ediciones Journal. Segunda edición. 2011.Vera M. Segmentación de estructuras cardiacas en imágenes de tomografía computarizada multi-corte. Ph.D. dissertation, Universidad de los Andes, Mérida-Venezuela, 2014.Vera M., Huérfano Y., Contreras J., Vera M. I., Salazar W., Vargas S., Chacón J. y Rodríguez J. (2017). Detección de hemorragia intracraneal intraparenquimatosa, en imágenes de tomografía computarizada cerebral, usando una técnica computacional no lineal. Latinoamericana de Hipertensión. 12(5), 125-130.ORIGINALPDF.pdfPDF.pdfPDFapplication/pdf706224https://bonga.unisimon.edu.co/bitstreams/27cf5264-e8d9-45ff-adf1-a8499554ca9f/download8b1313aaacc7becfff547417bd074f72MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-8368https://bonga.unisimon.edu.co/bitstreams/c5fd2418-1ab6-4c99-b99e-0005388313bf/download3fdc7b41651299350522650338f5754dMD52TEXTAssessment of methods for volumetric.pdf.txtAssessment of methods for volumetric.pdf.txtExtracted texttext/plain23840https://bonga.unisimon.edu.co/bitstreams/058e03d9-9205-4aa6-a99a-3d699ea6d0bc/download9208742657b3aca9fc8229fc82545449MD53PDF.pdf.txtPDF.pdf.txtExtracted texttext/plain24236https://bonga.unisimon.edu.co/bitstreams/281f708e-0091-4a2b-9e97-e0f0c1bea0a9/download921a76b60a427f086fdfca6ef9657697MD55THUMBNAILAssessment of methods for volumetric.pdf.jpgAssessment of methods for volumetric.pdf.jpgGenerated Thumbnailimage/jpeg1979https://bonga.unisimon.edu.co/bitstreams/e58fc768-e953-4053-8f95-f5f05bd6d817/downloadce2a487653bf26bcfa947b33ef7bfc94MD54PDF.pdf.jpgPDF.pdf.jpgGenerated Thumbnailimage/jpeg6895https://bonga.unisimon.edu.co/bitstreams/9fe88fa2-3729-43ba-b137-32a83ab9901e/download208ca406ae29683f960fd87fa9a68529MD5620.500.12442/2520oai:bonga.unisimon.edu.co:20.500.12442/25202024-08-14 21:53:17.595open.accesshttps://bonga.unisimon.edu.coRepositorio Digital Universidad Simón Bolívarrepositorio.digital@unisimon.edu.coPGEgcmVsPSJsaWNlbnNlIiBocmVmPSJodHRwOi8vY3JlYXRpdmVjb21tb25zLm9yZy9saWNlbnNlcy9ieS1uYy80LjAvIj48aW1nIGFsdD0iTGljZW5jaWEgQ3JlYXRpdmUgQ29tbW9ucyIgc3R5bGU9ImJvcmRlci13aWR0aDowIiBzcmM9Imh0dHBzOi8vaS5jcmVhdGl2ZWNvbW1vbnMub3JnL2wvYnktbmMvNC4wLzg4eDMxLnBuZyIgLz48L2E+PGJyLz5Fc3RhIG9icmEgZXN0w6EgYmFqbyB1bmEgPGEgcmVsPSJsaWNlbnNlIiBocmVmPSJodHRwOi8vY3JlYXRpdmVjb21tb25zLm9yZy9saWNlbnNlcy9ieS1uYy80LjAvIj5MaWNlbmNpYSBDcmVhdGl2ZSBDb21tb25zIEF0cmlidWNpw7NuLU5vQ29tZXJjaWFsIDQuMCBJbnRlcm5hY2lvbmFsPC9hPi4=