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dc.contributor.authorLiew, AWC
dc.contributor.authorYan, H
dc.contributor.editorCornelius T. Leondes
dc.date.accessioned2017-05-03T15:20:06Z
dc.date.available2017-05-03T15:20:06Z
dc.date.issued2005
dc.date.modified2009-07-29T06:07:22Z
dc.identifier.isbn9789812569899
dc.identifier.urihttp://hdl.handle.net/10072/24903
dc.description.abstractThe segmentation of magnetic resonance (MR) brain images is an important problem in medical imaging. Accurate segmentation of MR brain images allows a detail study of 3D brain tissue anatomy. It is also of great interest in the study of many brain disorders, where accurate volumetric measurement of the disorders is often required. In view of the importance of the task, much effort has been spent on finding accurate and efficient algorithms for the MRI segmentation problem. This chapter attempts to give the readers an overview of the MR brain segmentation problem, the various image artifacts that are often encountered, and describe some of the current approaches in this area, as well as our own work. To facilitate discussion, we broadly divide current MR brain image segmentation algorithms into three categories: classification-based, region-based, and contour-based methods, and discuss the merits and limitations of these approaches. Following a review of existing methods, we describe our approach for MR brain image segmentation in detail. Our approach is based on a clustering-for-classification framework, using a novel variant of the fuzzy c-means algorithm. We show that by incorporating two key ideas into the clustering algorithm, we are able to take into account the local spatial context, to compensate for the intensity nonuniformity artifact and the partial volume averaging artifact, and to reduce the influence of image noise, during the segmentation process. Extensive experiment results on both simulated and real MR brain images are given to illustrate the effectiveness and robustness of our approach. We conclude this chapter by pointing to some possible future directions in this area.
dc.description.publicationstatusYes
dc.languageEnglish
dc.language.isoeng
dc.publisherWorld Scientific Publishing Company
dc.publisher.placeUSA
dc.relation.ispartofbooktitleMedical Imaging Systems Technology: Methods in Cardiovascular and Brain Systems
dc.relation.ispartofchapter10
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom307
dc.relation.ispartofpageto357
dc.rights.retentionY
dc.subject.fieldofresearchcode280203
dc.subject.fieldofresearchcode291599
dc.titleComputer Techniques for the Automatic Segmentation of 3D MR Brain Images
dc.typeBook chapter
dc.type.descriptionB2 - Chapters (Other)
dc.type.codeB - Book Chapters
gro.date.issued2005
gro.hasfulltextNo Full Text
gro.griffith.authorLiew, Alan Wee-Chung


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