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)
Tessamma, Thomas; Ananda Resmi, S(Scientific Research Publishing, July 28, 2012)
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Abstract:
This work presents an efficient method for volume rendering of glioma tumors from segmented 2D MRI Datasets with user interactive control, by replacing manual segmentation required in the state of art methods. The most common primary brain tumors are gliomas, evolving from the cerebral supportive cells. For clinical follow-up, the evaluation of the pre- operative tumor volume is essential. Tumor portions were automatically segmented from 2D MR images using morphological filtering techniques. These seg- mented tumor slices were propagated and modeled with the software package. The 3D modeled tumor consists of gray level values of the original image with exact tumor boundary. Axial slices of FLAIR and T2 weighted images were used for extracting tumors. Volumetric assessment of tumor volume with manual segmentation of its outlines is a time-consuming proc- ess and is prone to error. These defects are overcome in this method. Authors verified the performance of our method on several sets of MRI scans. The 3D modeling was also done using segmented 2D slices with the help of a medical software package called 3D DOCTOR for verification purposes. The results were validated with the ground truth models by the Radi- ologist.
Description:
J. Biomedical Science and Engineering, 2012, 5, 378-383