干旱区生态环境知识资源中心(Arid): A fully automatic methodology for MRI brain tumour detection and segmentation

Arid

DOI	10.1080/13682199.2018.1545412
	A fully automatic methodology for MRI brain tumour detection and segmentation
	Kebir, S. Tchoketch 1; Mekaoui, S.1; Bouhedda, M.2
通讯作者	Kebir, S. Tchoketch
来源期刊	IMAGING SCIENCE JOURNAL
ISSN	1368-2199
EISSN	1743-131X
出版年	2019
卷号	67 期号:1 页码:42-62
英文摘要	In this paper, a complete and fully automatic MRI brain tumour detection and segmentation methodology is presented as an efficient clinical-aided tool using Gaussian mixture model, Fuzzy C-Means, active contour, wavelet transform and entropy segmentation methods. The proposed algorithm is based on two main parts: the skull stripping and tumour auto-detection and segmentation. The first part was evaluated using IBSR, LPBA40 and OASIS databases, and the obtained results show that our proposed method outclasses the best popular algorithms of brain extraction with scores of 0.913, 0.954 and 0.957 for the Jaccard index, Dice coefficient and sensitivity, respectively. The second part has been evaluated using BRATS database; this methodology has achieved an accuracy of 69% of true detection, and a false detection is around 22% of healthy cases detected as tumour cases and a false detection is around 9% of tumour cases detected as healthy cases. So, the tumour segmentation performed 0.67 Jaccard index and 0.69 Dice coefficient. Our methodology is found to be a fast, effective, accurate and fully automatic one without the need to any human interaction and prior knowledge for training phases as supervised methodologies in clinical applications.
英文关键词	Skull stripping brain tumour detection and segmentation Gaussian mixture model Fuzzy C-Means stationary wavelet maxima entropy segmentation
类型	Article
语种	英语
国家	Algeria
收录类别	SCI-E
WOS记录号	WOS:000455481000005
WOS关键词	IMAGE FUSION ; WAVELET ; FUZZY
WOS类目	Imaging Science & Photographic Technology
WOS研究方向	Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/216262
作者单位	1.USTHB, Lab Speech Commun & Signal Proc LCPTS, Algiers, Algeria; 2.Univ Medea, Lab Adv Elect Syst LSEA, Medea, Algeria
推荐引用方式 GB/T 7714	Kebir, S. Tchoketch,Mekaoui, S.,Bouhedda, M.. A fully automatic methodology for MRI brain tumour detection and segmentation[J],2019,67(1):42-62.
APA	Kebir, S. Tchoketch,Mekaoui, S.,&Bouhedda, M..(2019).A fully automatic methodology for MRI brain tumour detection and segmentation.IMAGING SCIENCE JOURNAL,67(1),42-62.
MLA	Kebir, S. Tchoketch,et al."A fully automatic methodology for MRI brain tumour detection and segmentation".IMAGING SCIENCE JOURNAL 67.1(2019):42-62.