Please use this identifier to cite or link to this item: https://dspace.upt.ro/xmlui/handle/123456789/3838
Title: Fuzzy automatic classification and without a prior knowledge - mean shift application to MRI brain images segmentation [articol]
Authors: Moussaoui, A.
Chen, V.
Subjects: Fuzzy c-means
Mean shift
Image segmentation
Issue Date: 2004
Publisher: Timişoara : Editura Politehnica
Citation: Moussaoui, A.. Fuzzy automatic classification and without a prior knowledge - mean shift application to MRI brain images segmentation. Timişoara: Editura Politehnica, 2004
Series/Report no.: Buletinul ştiinţific al Universităţii „Politehnica” din Timişoara, România. Seria electronică şi telecomunicaţii, Tom 49(63), fasc. 1 (2004), p. 199-204
Abstract: The objective of this paper is to propose a blind segmentation method able to localize all relevant objects in medical images by using a fuzzy classification based mean shift algorithm. To achieve this, we have to build a cartography of attributes consequent upon images characterization. The objects localization is realized by searching modes from a point sample distribution through mean shift procedure. In order to obtain an image automatic segmentation, the approach is joined at a fuzzy classification based fuzzy c-means (FCM) approach. The fuzzy insertion here allows to take into account imprecision related to information extraction which is necessary for a region classification. Actually, the obtained results by our approach are very encouraging and show an accurate segmentation compared to others supervised techniques.
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Appears in Collections:Articole științifice/Scientific articles

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