MRI skull stripping and tissue segmentation using conventional methods and different available tools

1. Data set references

   https://ida.loni.usc.edu/

   https://drive.google.com/drive/folders/1D4Oih54PM8fMduoDtg_AI1wBpPRgxW4w?usp=sharing

   https://drive.google.com/drive/folders/15Z5vt7b1fXXepfDeU7ZduT8-e1eHXNdQ?usp=sharing

2. Basic skull stripping using conventional image processing algorithm

   i) Using Otsu Thresholding and connected component analysis

   ii) Using Active Contour

3. Segment Hemisphere: Using Hough Transform

4. Grouping of tissue (wm, gm, ventricles, csf, …) Using Traditional Image Processing Algorithms:

   i) INTENSITY BASED METHODS:

    a) THRESHOLDING TECHNIQUE(LOCAL,GLOBAL,ADAPTIVE)(Multi Otsu Thresholding)
   

   ii) CLUSTERING BASED SEGMENTATION:

    a) K-means clustering
    
    b) Fuzzy C-means Clustering
    
    c) Gaussian Mixture Model
    
    d) Watershed Segmentation
   

   iii) Advanced Grouping of Tissues (wm, gm, ventricles, csf, …) with

    a) Free Surfer : https://www.opensourceimaging.org/project/freesurfer/
    
    b) Robex : https://www.nitrc.org/projects/robex
    
    c) ANTPY : https://github.com/ntustison/KapowskiChronicles
   

   iv) Comparison by evaluation metrics : Hausdorff distance, DICE, JC, Accuracy