Paper Details: Downloads: 482
Serial Number: P1150912682
Title: Semi-automatic Segmentation of MRI Brain Tumor
Authors: R. B. Dubey and M. Hanmandlu and S. K. Gupta and S. K. Gupta
Abstract: A semi-automatic method has been developed for segmentation of brain tumor from MR images. Segmentation of 3-D tumor structures from magnetic resonance images (MRI) is a very challenging problem due to the variability of tumor geometry and intensity patterns. Level set evolution combining global smoothness with the flexibility of topology changes offers significant advantages over the conventional statistical classification followed by mathematical morphology. Level set evolution with constant propagation needs to be initialized either completely inside or outside and can leak through weak or missing boundary parts. Replacing the constant propagation term by a statistical force overcomes these limitations and results in a region converge to a stable solution. MR images presenting tumors, probabilities for background and tumor regions are calculated from a pre- and post-contrast difference image and mixture-modeling fit of the histogram. The whole image is used for initialization of the level set evolution to segment the tumor boundaries. Results on two cases presenting different tumors with significant shape and intensity variability show that the method might become a powerful and efficient tool for the clinic. Validity is demonstrated by comparison with manual expert radiologist.
Keywords: Level set evaluation, medical image processing, MRI, tumor segmentation.
Journal/Conference: International Journal of Graphics, Vision and Image Processing
Volume: 9
Issue: 4
Submission Date: 3/15/2009 12:00:00 AM
Review Date: 5/4/2009 12:00:00 AM
Publishing Date: 5/25/2009 12:00:00 AM
Article Downloads: 482
Download:

Facebook