Published in: 13th Iranian conference on Biomedical Engineering
COI code: ICBME13_004
Paper Language: English
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Authors Coupled Object Segmentation Using Entropy and Fuzzy Characteristics of TissuesP Bahman Bijari -
A Akhoundi Asl -
H Soltanian-Zadeh -
Abstract:In this paper, we introduce a novel method based on level sets and fuzzy c-means clustering methods for the segmentation of medical images. Our new multi-structural method integrates the Herbulot’s entropy minimization and fuzzy forces. We introduce a prior shape based on the tissue segmentation results of each image. This incorporates interactive knowledge-based evolution that increases the accuracy and alleviates the need for the prior statistical information about the shapes of the structures. We have applied the proposed method to segment ventricles, caudate, and putamen in magnetic resonance images (MRI) of the brain. Comparative results show the benefits of the proposed constraints. Accurate results and independency from the initialization are obtained when using the proposed method.
COI code: ICBME13_004
how to cite to this paper:If you want to refer to this article in your research, you can easily use the following in the resources and references section:
Bahman Bijari, P; A Akhoundi Asl & H Soltanian-Zadeh, 2006, Coupled Object Segmentation Using Entropy and Fuzzy Characteristics of Tissues, 13th Iranian conference on Biomedical Engineering, تهران, انجمن مهندسي پزشكي ايران, دانشگاه صنعتي شريف, https://www.civilica.com/Paper-ICBME13-ICBME13_004.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Bahman Bijari, P; A Akhoundi Asl & H Soltanian-Zadeh, 2006)
Second and more: (Bahman Bijari; Akhoundi Asl & Soltanian-Zadeh, 2006)
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