Hybridization Techniques To Detect Brain Tumor

  • Muhammad Abrar BZU Multan
  • Asif Hussain NCBA&E
  • Roha Masroor NCBA&E
  • Ifra Masroor NCBA&E

Abstract

Diagnosing brain tumor in present era through digital techniques need serious attention as the number of patients are increasing in an awkward manner. Magnetic Resonance Imaging is the tool that is used for detection of brain tumors. This paper is classified in two phases i.e. normal and abnormal brain images. Then, Feature selection and classification are applied on the given data set. Classification on given data set is done through K- Nearest Neighbor. In the given study, we have taken normal and abnormal samples from Nishtar Medical hospital, Multan. In order to classify brain images, first it needs to pre-process through skull stripping technique then the proposed algorithm is followed. Algorithm involves feature extraction through GLCM and feature selection through ACO. Results have proved its efficiency level up-to 88%.

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Published
2021-01-05
How to Cite
ABRAR, Muhammad et al. Hybridization Techniques To Detect Brain Tumor. Sukkur IBA Journal of Computing and Mathematical Sciences, [S.l.], v. 4, n. 2, p. 28-37, jan. 2021. ISSN 2522-3003. Available at: <http://journal.iba-suk.edu.pk:8089/SIBAJournals/index.php/sjcms/article/view/655>. Date accessed: 19 apr. 2021. doi: https://doi.org/10.30537/sjcms.v4i2.655.