Three-dimensional segmentation of brain aneurysms in CTA using non-parametric region-based information and implicit deformable models: Method and evaluation

Monica Hernandez; Alejandro F. Frangi; Guillermo Sapiro

doi:10.1007/978-3-540-39903-2_73

Three-dimensional segmentation of brain aneurysms in CTA using non-parametric region-based information and implicit deformable models: Method and evaluation

Monica Hernandez^*, Alejandro F. Frangi, Guillermo Sapiro

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

Abstract

Knowledge of brain aneurysm dimensions is essential in minimally invasive surgical interventions using Guglielmi Detachable Coils. These parameters are obtained in clinical routine using 2D maximum intensity projection images. Automated quantification of the three dimensional structure of aneurysms directly from the 3D data set may be used to provide accurate and objective measurements of the clinically relevant parameters. In this paper we present an algorithm devised for the segmentation of brain aneurysms based on implicit deformable models combined with non-parametric region-based information. This work also presents the evaluation of the method in a clinical data base of 39 cases.

Original language	English
Pages (from-to)	594-602
Number of pages	9
Journal	Lecture notes in computer science
Volume	2879
Issue number	PART 2
DOIs	https://doi.org/10.1007/978-3-540-39903-2_73
Publication status	Published - 2003
Event	Medical Image Computing and Computer-Assisted Intervention, MICCAI 2003 - 6th International Conference Proceedings - Montreal, Que., Canada Duration: 15 Nov 2003 → 18 Nov 2003

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10.1007/978-3-540-39903-2_73

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title = "Three-dimensional segmentation of brain aneurysms in CTA using non-parametric region-based information and implicit deformable models: Method and evaluation",

abstract = "Knowledge of brain aneurysm dimensions is essential in minimally invasive surgical interventions using Guglielmi Detachable Coils. These parameters are obtained in clinical routine using 2D maximum intensity projection images. Automated quantification of the three dimensional structure of aneurysms directly from the 3D data set may be used to provide accurate and objective measurements of the clinically relevant parameters. In this paper we present an algorithm devised for the segmentation of brain aneurysms based on implicit deformable models combined with non-parametric region-based information. This work also presents the evaluation of the method in a clinical data base of 39 cases.",

author = "Monica Hernandez and Frangi, \{Alejandro F.\} and Guillermo Sapiro",

year = "2003",

doi = "10.1007/978-3-540-39903-2\_73",

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journal = "Lecture notes in computer science",

issn = "0302-9743",

publisher = "Springer Nature",

number = "PART 2",

note = "Medical Image Computing and Computer-Assisted Intervention, MICCAI 2003 - 6th International Conference Proceedings ; Conference date: 15-11-2003 Through 18-11-2003",

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Three-dimensional segmentation of brain aneurysms in CTA using non-parametric region-based information and implicit deformable models: Method and evaluation. / Hernandez, Monica; Frangi, Alejandro F.; Sapiro, Guillermo.
In: Lecture notes in computer science, Vol. 2879, No. PART 2, 2003, p. 594-602.

Research output: Contribution to journal › Conference article › peer-review

TY - JOUR

T1 - Three-dimensional segmentation of brain aneurysms in CTA using non-parametric region-based information and implicit deformable models

T2 - Medical Image Computing and Computer-Assisted Intervention, MICCAI 2003 - 6th International Conference Proceedings

AU - Hernandez, Monica

AU - Frangi, Alejandro F.

AU - Sapiro, Guillermo

PY - 2003

Y1 - 2003

N2 - Knowledge of brain aneurysm dimensions is essential in minimally invasive surgical interventions using Guglielmi Detachable Coils. These parameters are obtained in clinical routine using 2D maximum intensity projection images. Automated quantification of the three dimensional structure of aneurysms directly from the 3D data set may be used to provide accurate and objective measurements of the clinically relevant parameters. In this paper we present an algorithm devised for the segmentation of brain aneurysms based on implicit deformable models combined with non-parametric region-based information. This work also presents the evaluation of the method in a clinical data base of 39 cases.

AB - Knowledge of brain aneurysm dimensions is essential in minimally invasive surgical interventions using Guglielmi Detachable Coils. These parameters are obtained in clinical routine using 2D maximum intensity projection images. Automated quantification of the three dimensional structure of aneurysms directly from the 3D data set may be used to provide accurate and objective measurements of the clinically relevant parameters. In this paper we present an algorithm devised for the segmentation of brain aneurysms based on implicit deformable models combined with non-parametric region-based information. This work also presents the evaluation of the method in a clinical data base of 39 cases.

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JO - Lecture notes in computer science

JF - Lecture notes in computer science

IS - PART 2

Y2 - 15 November 2003 through 18 November 2003

ER -

Three-dimensional segmentation of brain aneurysms in CTA using non-parametric region-based information and implicit deformable models: Method and evaluation

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