Automatic segmentation framework for primary tumors from brain MRIs using morphological filtering techniques
Author(s) -
Resmi S. Ananda,
Tessamma Thomas
Publication year - 2013
Publication title -
2012 5th international conference on biomedical engineering and informatics
Language(s) - English
Resource type - Conference proceedings
ISBN - 978-1-4673-1184-7
DOI - 10.1109/bmei.2012.6512995
Subject(s) - bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing
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.
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