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Fuzzy-based extraction of vascular structures from time-of-flight MR images.

Standard

Fuzzy-based extraction of vascular structures from time-of-flight MR images. / Forkert, Nils Daniel; Säring, Dennis; Wenzel, Karolin; Illies, Till; Fiehler, Jens; Handels, Heinz.

in: Stud Health Technol Inform, Jahrgang 150, 2009, S. 816-820.

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

Harvard

Forkert, ND, Säring, D, Wenzel, K, Illies, T, Fiehler, J & Handels, H 2009, 'Fuzzy-based extraction of vascular structures from time-of-flight MR images.', Stud Health Technol Inform, Jg. 150, S. 816-820. <http://www.ncbi.nlm.nih.gov/pubmed/19745426?dopt=Citation>

APA

Forkert, N. D., Säring, D., Wenzel, K., Illies, T., Fiehler, J., & Handels, H. (2009). Fuzzy-based extraction of vascular structures from time-of-flight MR images. Stud Health Technol Inform, 150, 816-820. http://www.ncbi.nlm.nih.gov/pubmed/19745426?dopt=Citation

Vancouver

Forkert ND, Säring D, Wenzel K, Illies T, Fiehler J, Handels H. Fuzzy-based extraction of vascular structures from time-of-flight MR images. Stud Health Technol Inform. 2009;150:816-820.

Bibtex

@article{5c6e4f316a3f41679158b0bdf18c050c,
title = "Fuzzy-based extraction of vascular structures from time-of-flight MR images.",
abstract = "In this paper an automatic fuzzy based method for the extraction of the cerebrovascular system from 3D Time-of-Flight (TOF) MRA image sequences is presented. In order to exclude non-brain tissue an automatic skull stripping method is applied in a preprocessing step. Based on the TOF images vesselness and maximum parameter images are computed first. These parameter images are then combined with the TOF sequence using a fuzzy inference. The resulting fuzzy image offers an improved enhancement of small as well as malformed vessels against the remaining brain. Finally, the fuzzy-connectedness approach is used to extract the vascular system. A first evaluation showed that the fuzzy-based method proposed performs better than a state of the art method and yields results in the range of the inter-observer variation.",
author = "Forkert, {Nils Daniel} and Dennis S{\"a}ring and Karolin Wenzel and Till Illies and Jens Fiehler and Heinz Handels",
year = "2009",
language = "Deutsch",
volume = "150",
pages = "816--820",

}

RIS

TY - JOUR

T1 - Fuzzy-based extraction of vascular structures from time-of-flight MR images.

AU - Forkert, Nils Daniel

AU - Säring, Dennis

AU - Wenzel, Karolin

AU - Illies, Till

AU - Fiehler, Jens

AU - Handels, Heinz

PY - 2009

Y1 - 2009

N2 - In this paper an automatic fuzzy based method for the extraction of the cerebrovascular system from 3D Time-of-Flight (TOF) MRA image sequences is presented. In order to exclude non-brain tissue an automatic skull stripping method is applied in a preprocessing step. Based on the TOF images vesselness and maximum parameter images are computed first. These parameter images are then combined with the TOF sequence using a fuzzy inference. The resulting fuzzy image offers an improved enhancement of small as well as malformed vessels against the remaining brain. Finally, the fuzzy-connectedness approach is used to extract the vascular system. A first evaluation showed that the fuzzy-based method proposed performs better than a state of the art method and yields results in the range of the inter-observer variation.

AB - In this paper an automatic fuzzy based method for the extraction of the cerebrovascular system from 3D Time-of-Flight (TOF) MRA image sequences is presented. In order to exclude non-brain tissue an automatic skull stripping method is applied in a preprocessing step. Based on the TOF images vesselness and maximum parameter images are computed first. These parameter images are then combined with the TOF sequence using a fuzzy inference. The resulting fuzzy image offers an improved enhancement of small as well as malformed vessels against the remaining brain. Finally, the fuzzy-connectedness approach is used to extract the vascular system. A first evaluation showed that the fuzzy-based method proposed performs better than a state of the art method and yields results in the range of the inter-observer variation.

M3 - SCORING: Zeitschriftenaufsatz

VL - 150

SP - 816

EP - 820

ER -