干旱区生态环境知识资源中心(Arid): A Fuzzy Consensus Clustering Algorithm for MRI Brain Tissue Segmentation

Arid

DOI	10.3390/app12157385
	A Fuzzy Consensus Clustering Algorithm for MRI Brain Tissue Segmentation
	Kumar, S. V. Aruna; Yaghoubi, Ehsan; Proenca, Hugo
通讯作者	Kumar, SVA
来源期刊	APPLIED SCIENCES-BASEL
EISSN	2076-3417
出版年	2022
卷号	12 期号:15
英文摘要	Brain tissue segmentation is an important component of the clinical diagnosis of brain diseases using multi-modal magnetic resonance imaging (MR). Brain tissue segmentation has been developed by many unsupervised methods in the literature. The most commonly used unsupervised methods are K-Means, Expectation-Maximization, and Fuzzy Clustering. Fuzzy clustering methods offer considerable benefits compared with the aforementioned methods as they are capable of handling brain images that are complex, largely uncertain, and imprecise. However, this approach suffers from the intrinsic noise and intensity inhomogeneity (IIH) in the data resulting from the acquisition process. To resolve these issues, we propose a fuzzy consensus clustering algorithm that defines a membership function resulting from a voting schema to cluster the pixels. In particular, we first pre-process the MRI data and employ several segmentation techniques based on traditional fuzzy sets and intuitionistic sets. Then, we adopted a voting schema to fuse the results of the applied clustering methods. Finally, to evaluate the proposed method, we used the well-known performance measures (boundary measure, overlap measure, and volume measure) on two publicly available datasets (OASIS and IBSR18). The experimental results show the superior performance of the proposed method in comparison with the recent state of the art. The performance of the proposed method is also presented using a real-world Autism Spectrum Disorder Detection problem with better accuracy compared to other existing methods.
英文关键词	brain tissue segmentation consensus clustering segmentation magnetic resonance image
类型	Article
语种	英语
开放获取类型	gold, Green Submitted
收录类别	SCI-E
WOS记录号	WOS:000839328900001
WOS关键词	C-MEANS ; IMAGE SEGMENTATION ; RANDOM FORESTS ; CLASSIFICATION ; MODEL
WOS类目	Chemistry, Multidisciplinary ; Engineering, Multidisciplinary ; Materials Science, Multidisciplinary ; Physics, Applied
WOS研究方向	Chemistry ; Engineering ; Materials Science ; Physics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/391863
推荐引用方式 GB/T 7714	Kumar, S. V. Aruna,Yaghoubi, Ehsan,Proenca, Hugo. A Fuzzy Consensus Clustering Algorithm for MRI Brain Tissue Segmentation[J],2022,12(15).
APA	Kumar, S. V. Aruna,Yaghoubi, Ehsan,&Proenca, Hugo.(2022).A Fuzzy Consensus Clustering Algorithm for MRI Brain Tissue Segmentation.APPLIED SCIENCES-BASEL,12(15).
MLA	Kumar, S. V. Aruna,et al."A Fuzzy Consensus Clustering Algorithm for MRI Brain Tissue Segmentation".APPLIED SCIENCES-BASEL 12.15(2022).