Open AccessBrain Tumor Detection using Image Processing
Author(s) -
C Nithyasree,
Damian Stanley,
K Subalakshmi
Publication year - 2021
Publication title -
international journal on cybernetics and informatics/international journal of cybernetics and informatics
Language(s) - English
Resource type - Journals
eISSN - 2320-8430
pISSN - 2277-548X
DOI - 10.5121/ijci.2021.100235
Subject(s) - cluster analysis , segmentation , artificial intelligence , computer science , image segmentation , k means clustering , image processing , magnetic resonance imaging , pattern recognition (psychology) , medical imaging , brain tumor , image (mathematics) , computer vision , watershed , medicine , radiology , pathology
Brain tumor extraction and its analysis are challenging tasks in medical image processing because brain image is complicated .Segmentation plays a very important role in the medical image processing.In that way MRI (magnetic resonance imaging )has become a useful medical diagnostic tool or the diagnosis o brain & other medical images.In this project, we are presenting a comparative study of three segmentation methods implemented or tumor detection .The method includes kmeans clustering using watershed algorithm . Optimized k-means and optimized c-means using genetic algorithm.