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Image Segmentation using Canny Edge and finding the Tumor Area in Image using Hierarchical Clustering

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Bandana Bali, Brij Mohan Singh
10.5120/ijca2017914234

Bandana Bali and Brij Mohan Singh. Image Segmentation using Canny Edge and finding the Tumor Area in Image using Hierarchical Clustering. International Journal of Computer Applications 167(4):9-12, June 2017. BibTeX

@article{10.5120/ijca2017914234,
	author = {Bandana Bali and Brij Mohan Singh},
	title = {Image Segmentation using Canny Edge and finding the Tumor Area in Image using Hierarchical Clustering},
	journal = {International Journal of Computer Applications},
	issue_date = {June 2017},
	volume = {167},
	number = {4},
	month = {Jun},
	year = {2017},
	issn = {0975-8887},
	pages = {9-12},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume167/number4/27758-2017914234},
	doi = {10.5120/ijca2017914234},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

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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Keywords

Brain, MRI, Magnetic Resonance Imaging, Segmentation, Algorithm, Tumor, Highlight.