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Now-a-days with the use of medical field, the use of technology has increased too much. Automatic detection of brain tumor is a very difficult task. Due to variations in type, size, location and shape of tumors it is difficult to detect accurate result of the tumour without the help of technology. In this paper, first the dataset of MRI scan image is taken as input and it is preprocessed using median filter. After preprocessing of images, the detection and extraction of region like tumour identification and segmentation of brain tumour is done. The segmentation which further introduces two-step procedure technique; i.e. the HCSD (Hierarchical centroid shape descriptor) and K-mean clustering. The methods incorporates with some noise removal technique, skull removal, thresholding which are some basic concepts of image processing of brain tumour. Using MATLAB Software detection and extraction of tumour from MRI scan images of the brain is done.
Keywords:
Brain tumour, MRI Image, Segmentation, HCSD, K- means clustering, MATLAB.
Cite Article:
"Automatic Brain Tumour Detection", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.5, Issue 4, page no.17 - 18, April-2020, Available :http://www.ijrti.org/papers/IJRTI2004004.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator