Brain Tumor Extraction and Classification from MRI Images
Smriti Bhatnagar1, Shubham Sharma2
1Smriti Bhatnagar, Department of Electronics and Communication, Jaypee Institute of Information Technology, Noida (U.P), India.
2Shubham Sharma, Department of Electronics and Communication, Jaypee Institute of Information Technology, Noida (U.P), India.
Manuscript received on 27 August 2019 | Revised Manuscript received on 03 September 2019 | Manuscript Published on 14 September 2019 | PP: 477-481 | Volume-8 Issue-5S3, July 2019 | Retrieval Number: E10990785S319/19©BEIESP | DOI: 10.35940/ijeat.E1099.0785S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: This paper proposes a methodology in which detection, extraction and classification of brain tumour is done with the help of a patient’s MRI image. Processing of medical images is currently a huge emerging issue and it has attracted lots of research all over the globe. Several techniques have been developed so far to process the images efficiently and extract out their important features. The paper describes certain strategies including some noise removal filters, grayscaling, segmentation along with morphological operations which are needed to extract out the features from the input image and SVM classifier for classification purpose.
Keywords: Grayscaling, MRI, Morphological Operations, MATLAB, Segmentation, SVM Classifier.
Scope of the Article: Classification