Automatic segmentation framework for primary tumors from brain MRIs using morphological filtering techniques

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....

Full description

Saved in:
Bibliographic Details
Published in2012 5th International Conference on Biomedical Engineering and Informatics pp. 238 - 242
Main Authors Ananda, Resmi S., Thomas, Tessamma
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2012
Subjects
Brain MRI
Dilation
Erosion
Morphological filtering
Primary tumor
Segmentation
Tumor boundary
Online AccessGet full text

Cover

More Information
Summary: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.
ISBN:9781467311830
1467311839
DOI:10.1109/BMEI.2012.6512995