Image Segmentation using Canny Edge and finding the Tumor Area in Image using Hierarchical Clustering
Author(s) -
Bandana Bali,
Brij Mohan
Publication year - 2017
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2017914234
Subject(s) - computer science , canny edge detector , artificial intelligence , image (mathematics) , computer vision , cluster analysis , image segmentation , enhanced data rates for gsm evolution , hierarchical clustering , image gradient , segmentation , pattern recognition (psychology) , edge detection , image processing , image texture
Image segmentation of Brain MRI holds great significance in the determination of valuable functional and anatomical information of a disease like tumors. It not only advances the diagnostic techniques but also proves to be of enormous facilitation in the planning of treatment. In this research paper, we will be utilizing the bilateral filter technique to eliminate noise from the brain magnetic resonance imaging images, following by applying the improved canny edge detection algorithm for image segmentation to locate the ridges of tumor areas in them. The last step of hierarchical clustering algorithm application will aid in highlighting the affected area in the images thereby addressing the issues of clear location of tumor cells in the brain MRI images.
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