NDLI: 3D brain tumor segmentation scheme using K-mean clustering and connected component labeling algorithms

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3D brain tumor segmentation scheme using K-mean clustering and connected component labeling algorithms

Content Provider	IEEE Xplore Digital Library
Author	Moftah, H.M. Hassanien, A.E. Shoman, M.
Copyright Year	2010
Description	Author affiliation: Cairo University Faculty of Computers and Information, Information Technology Department (Moftah, H.M.; Hassanien, A.E.; Shoman, M.)
Abstract	In the recent years human brain segmentation in three-dimensional magnetic resonance imaging (MRI) has gained a lot of importance in the field of biomedical image processing since it is the main stage for the automatic brain disease diagnosis. In this paper, we propose an image segmentation scheme to segment 3D brain tumor from MRI images through the clustering process. The clustering is achieved using K-mean algorithm in conjunction with the connected component labeling algorithm to link the similar clustered objects in all 2D slices and then obtain 3D segmented tissue using the patch object rendering process.
Starting Page	320
Ending Page	324
File Size	563837
Page Count	5
File Format	PDF
ISBN	9781424481347
e-ISBN	9781424481361
DOI	10.1109/ISDA.2010.5687244
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-11-29
Publisher Place	Egypt
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Magnetic resonance imaging Clustering algorithms Three dimensional displays Classification algorithms Labeling Tumors
Content Type	Text
Resource Type	Article

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