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Fuzzy-based vascular structure enhancement in Time-of-Flight MRA images for improved segmentation.

Standard

Fuzzy-based vascular structure enhancement in Time-of-Flight MRA images for improved segmentation. / Forkert, Nils; Schmidt-Richberg, Alexander; Fiehler, Jens; Illies, Till; Möller, D; Handels, Heinz; Säring, Dennis.

in: METHOD INFORM MED, Jahrgang 50, Nr. 1, 1, 2011, S. 74-83.

Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung

Harvard

Forkert, N, Schmidt-Richberg, A, Fiehler, J, Illies, T, Möller, D, Handels, H & Säring, D 2011, 'Fuzzy-based vascular structure enhancement in Time-of-Flight MRA images for improved segmentation.', METHOD INFORM MED, Jg. 50, Nr. 1, 1, S. 74-83. <http://www.ncbi.nlm.nih.gov/pubmed/21057718?dopt=Citation>

APA

Forkert, N., Schmidt-Richberg, A., Fiehler, J., Illies, T., Möller, D., Handels, H., & Säring, D. (2011). Fuzzy-based vascular structure enhancement in Time-of-Flight MRA images for improved segmentation. METHOD INFORM MED, 50(1), 74-83. [1]. http://www.ncbi.nlm.nih.gov/pubmed/21057718?dopt=Citation

Vancouver

Forkert N, Schmidt-Richberg A, Fiehler J, Illies T, Möller D, Handels H et al. Fuzzy-based vascular structure enhancement in Time-of-Flight MRA images for improved segmentation. METHOD INFORM MED. 2011;50(1):74-83. 1.

Bibtex

@article{232bf2a6842b4d5481d44835c631f33d,
title = "Fuzzy-based vascular structure enhancement in Time-of-Flight MRA images for improved segmentation.",
abstract = "Cerebral vascular malformations might lead to strokes due to occurrence of ruptures. The rupture risk is highly related to the individual vascular anatomy. The 3D Time-of-Flight (TOF) MRA technique is a commonly used non-invasive imaging technique for exploration of the vascular anatomy. Several clinical applications require exact cerebrovascular segmentations from this image sequence. For this purpose, intensity-based segmentation approaches are widely used. Since small low-contrast vessels are often not detected, vesselness filter-based segmentation schemes have been proposed, which contrariwise have problems detecting malformed vessels. In this paper, a fuzzy logic-based method for fusion of intensity and vesselness information is presented, allowing an improved segmentation of malformed and small vessels at preservation of advantages of both approaches.",
author = "Nils Forkert and Alexander Schmidt-Richberg and Jens Fiehler and Till Illies and D M{\"o}ller and Heinz Handels and Dennis S{\"a}ring",
year = "2011",
language = "English",
volume = "50",
pages = "74--83",
journal = "METHOD INFORM MED",
issn = "0026-1270",
publisher = "Schattauer",
number = "1",

}

RIS

TY - JOUR

T1 - Fuzzy-based vascular structure enhancement in Time-of-Flight MRA images for improved segmentation.

AU - Forkert, Nils

AU - Schmidt-Richberg, Alexander

AU - Fiehler, Jens

AU - Illies, Till

AU - Möller, D

AU - Handels, Heinz

AU - Säring, Dennis

PY - 2011

Y1 - 2011

N2 - Cerebral vascular malformations might lead to strokes due to occurrence of ruptures. The rupture risk is highly related to the individual vascular anatomy. The 3D Time-of-Flight (TOF) MRA technique is a commonly used non-invasive imaging technique for exploration of the vascular anatomy. Several clinical applications require exact cerebrovascular segmentations from this image sequence. For this purpose, intensity-based segmentation approaches are widely used. Since small low-contrast vessels are often not detected, vesselness filter-based segmentation schemes have been proposed, which contrariwise have problems detecting malformed vessels. In this paper, a fuzzy logic-based method for fusion of intensity and vesselness information is presented, allowing an improved segmentation of malformed and small vessels at preservation of advantages of both approaches.

AB - Cerebral vascular malformations might lead to strokes due to occurrence of ruptures. The rupture risk is highly related to the individual vascular anatomy. The 3D Time-of-Flight (TOF) MRA technique is a commonly used non-invasive imaging technique for exploration of the vascular anatomy. Several clinical applications require exact cerebrovascular segmentations from this image sequence. For this purpose, intensity-based segmentation approaches are widely used. Since small low-contrast vessels are often not detected, vesselness filter-based segmentation schemes have been proposed, which contrariwise have problems detecting malformed vessels. In this paper, a fuzzy logic-based method for fusion of intensity and vesselness information is presented, allowing an improved segmentation of malformed and small vessels at preservation of advantages of both approaches.

M3 - SCORING: Journal article

VL - 50

SP - 74

EP - 83

JO - METHOD INFORM MED

JF - METHOD INFORM MED

SN - 0026-1270

IS - 1

M1 - 1

ER -