Author:
Sweta Parkhedkar, priyanka malgi
Subject:
Communication
Material Type:
Module
Level:
Graduate / Professional
Tags:
  • Clustering
  • Edge Detection
  • Hesitation Degree
  • Intuitionistic Fuzzy Set (IFS)
  • Membership Function
  • Restricted Equivalence Function
  • Skull Stripping
  • Thresholding
  • License:
    Creative Commons Attribution Non-Commercial No Derivatives
    Language:
    English
    Media Formats:
    Downloadable docs

    Fuzzy logic

    Overview

    This project presents the method for the segmentation and detection of tumor of Magnetic Resonances brain images using intuitionistic fuzzy representation and intuitionistic fuzzy divergence method. In this proposed method, skull stripping is carried out for the removal of unwanted portion from the brain image using morphology.  A Restricted equivalence function from automorphisms is used for intuitionistic fuzzy representation of image. Sugeno type intuitionistic fuzzy generator is used to calculate non-membership and hesitation degree. A new distance measure, Intuitionistic Fuzzy Divergence is used to find the optimum threshold to detect the brain tumour from MR images. The results showed a much better performance on poor illuminated brain MR images, where the brain tumor is detected properly.

    Develop a program for skull stripping using matlab

    Algorithm for Skull Stripping:  

    1. take a input image of brain in JPEG

    2. perform thresholding on the image.

    3. perform morphological operation on the image

    4. use image enhancement techniques

    5. skull stripped final image will be displayed

    comparision of image should be displayed.