Segmentation of brain tumors

Brain tumors in mri images can be detected
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Updated 11 Jun 2015

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Image segmentation can be achieved in different ways those are
thresholding, region growing, water sheds and contours. The drawbacks of previous
methods can be overcome through proposed method. To extract information regarding
tumour, at first in the pre-processing level, the extra parts which are outside the skull
and don't have any helpful information are removed and then anisotropic diffusion
filter is applied to the MRI images to remove noise. By applying the fast bounding
box (FBB) algorithm, the tumour area is displayed on the MRI image with a bounding
box and the central part is selected as sample points for training of a One Class SVM
classifier. Then Support Vector Machine classifies the boundary and extracts the
tumour.

Cite As

chandra sekhar ravuri (2024). Segmentation of brain tumors (https://www.mathworks.com/matlabcentral/fileexchange/51154-segmentation-of-brain-tumors), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2014a
Compatible with any release
Platform Compatibility
Windows macOS Linux
Acknowledgements

Inspired: dip lab4

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Version Published Release Notes
1.0.0.0