Please use this identifier to cite or link to this item: http://dspace.univ-temouchent.edu.dz/handle/123456789/2717
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dc.contributor.authorHORCH, Imene-
dc.contributor.authorTAOULI, Chahrazed-
dc.date.accessioned2024-02-27T15:24:17Z-
dc.date.available2024-02-27T15:24:17Z-
dc.date.issued2015-
dc.identifier.citationhttps://theses.univ-temouchent.edu.dz/opac_css/doc_num.php?explnum_id=1927en_US
dc.identifier.urihttp://dspace.univ-temouchent.edu.dz/handle/123456789/2717-
dc.description.abstractSegmentation has become a fundamental step for the quantitative analysis of images in many brain diseases such as Cerebral Vascular Accident stroke ' . In this dissertation we develop methods for detection and removal of this condition which is based on derivates operators then active contour as : snake and level set and we will finish with a method proposed by us which combines with Level set methods derivates . The algorithms developed in this work are tested on a set of brain images .en_US
dc.subjectMRI image, stroke, Segmentation Active Contour Snake Level seten_US
dc.titleSegmentation des images médicales par contour actifen_US
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