Segmentation of brain tumors
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.
Citation pour cette source
chandra sekhar ravuri (2024). Segmentation of brain tumors (https://www.mathworks.com/matlabcentral/fileexchange/51154-segmentation-of-brain-tumors), MATLAB Central File Exchange. Récupéré le .
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- Image Processing and Computer Vision > Image Processing Toolbox > Image Segmentation and Analysis > Image Segmentation >
- Sciences > Neuroscience > Human Brain Mapping > MRI >
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Version | Publié le | Notes de version | |
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1.0.0.0 |