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Please use this identifier to cite or link to this item: http://purl.org/purl/4568

Title: Automatic Segmentation Framework for Primary Tumors From Brain MRIs Using Morphological Filtering Techniques
Authors: Tessamma, Thomas
Ananda Resmi, S
Keywords: Segmentation
Morphological filtering
Dilation
Erosion
Primary tumor
Tumor boundary
Brain MRI
Issue Date: 2012
Publisher: IEEE
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
Description: 2012 5th International Conference on BioMedical Engineering and Informatics (BMEI 2012)
URI: http://dyuthi.cusat.ac.in/purl/4568
Appears in Collections:Dr.Tessamma Thomas

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