Fuzzy clustering in segmentation of abdominal structures based on CT studies

Wojciech Wiecławek; Ewa Pietka

doi:10.1007/978-3-540-68168-7_9

Fuzzy clustering in segmentation of abdominal structures based on CT studies

Department of Medical Informatics and Artificial Intelligence (RIB/RIB1)

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

12 Citations (Scopus)

Abstract

In the current study a modification of the live-wire approach to image segmentation has been developed. A Fuzzy C-Means (FCM) clustering procedure has been implemented before the cost map function is defined. This shrinks the area to be searched resulting in a significant reduction of the computational complexity. The method has been employed to Computed Tomography (CT) studies. Segmentation of the abdomen structures has been performed in order to evaluate the method.

Original language	English
Title of host publication	Information Technologies in Biomedicine
Pages	93-104
Number of pages	12
DOIs	https://doi.org/10.1007/978-3-540-68168-7_9
Publication status	Published - 2008

Publication series

Name	Advances in Soft Computing
Volume	47
ISSN (Print)	1615-3871
ISSN (Electronic)	1860-0794

ASJC Scopus subject areas

Computer Science (miscellaneous)
Computational Mechanics
Computer Science Applications

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10.1007/978-3-540-68168-7_9

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abstract = "In the current study a modification of the live-wire approach to image segmentation has been developed. A Fuzzy C-Means (FCM) clustering procedure has been implemented before the cost map function is defined. This shrinks the area to be searched resulting in a significant reduction of the computational complexity. The method has been employed to Computed Tomography (CT) studies. Segmentation of the abdomen structures has been performed in order to evaluate the method.",

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AB - In the current study a modification of the live-wire approach to image segmentation has been developed. A Fuzzy C-Means (FCM) clustering procedure has been implemented before the cost map function is defined. This shrinks the area to be searched resulting in a significant reduction of the computational complexity. The method has been employed to Computed Tomography (CT) studies. Segmentation of the abdomen structures has been performed in order to evaluate the method.

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DO - 10.1007/978-3-540-68168-7_9

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T3 - Advances in Soft Computing

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ER -

Fuzzy clustering in segmentation of abdominal structures based on CT studies

Abstract

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