Automatic Segmentation Framework for Primary Tumors From Brain MRIs Using Morphological Filtering Techniques

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Automatic Segmentation Framework for Primary Tumors From Brain MRIs Using Morphological Filtering Techniques

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dc.contributor.author Tessamma, Thomas
dc.contributor.author Ananda Resmi, S
dc.date.accessioned 2014-08-12T09:02:36Z
dc.date.available 2014-08-12T09:02:36Z
dc.date.issued 2012
dc.identifier.uri http://dyuthi.cusat.ac.in/purl/4568
dc.description 2012 5th International Conference on BioMedical Engineering and Informatics (BMEI 2012) en_US
dc.description.abstract This paper describes a novel framework for automatic segmentation of primary tumors and its boundary from brain MRIs using morphological filtering techniques. This method uses T2 weighted and T1 FLAIR images. This approach is very simple, more accurate and less time consuming than existing methods. This method is tested by fifty patients of different tumor types, shapes, image intensities, sizes and produced better results. The results were validated with ground truth images by the radiologist. Segmentation of the tumor and boundary detection is important because it can be used for surgical planning, treatment planning, textural analysis, 3-Dimensional modeling and volumetric analysis en_US
dc.description.sponsorship Cochin University of Science and Technology en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.subject Segmentation en_US
dc.subject Morphological filtering en_US
dc.subject Dilation en_US
dc.subject Erosion en_US
dc.subject Primary tumor en_US
dc.subject Tumor boundary en_US
dc.subject Brain MRI en_US
dc.title Automatic Segmentation Framework for Primary Tumors From Brain MRIs Using Morphological Filtering Techniques en_US
dc.type Article en_US


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