Diagnosis of Brain Diseases using Neural Networks
Anagha Naga Krishna1, Tejashwini V2, Sudhamani M J3
1Ms. Anagha Naga Krishna, B.E., Department of Computer Science and Engineering, RNSIT, Bengaluru (Karnataka), India.
2Dr. M J Sudhamani, Assistant Professor, Department of Computer Science and Engineering, RNSIT, Bengaluru (Karnataka), India.
3Tejashwini V, Assistant Professor, Department of Computer Science and Engineering, RNSIT, Bengaluru (Karnataka), India.
Manuscript received on 05 December 2019 | Revised Manuscript received on 13 December 2019 | Manuscript Published on 31 December 2019 | PP: 402-407 | Volume-9 Issue-2S December 2019 | Retrieval Number: B10361292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1036.1292S19
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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: Intensification in the occurrence of brain diseases and the need for the initial diagnosis for ailments like Tumor, Alzheimer’s, Epilepsy and Parkinson’s has riveted the attention of researchers. Machine learning practices, specifically deep learning, is considered as a beneficial diagnostic tool. Deep learning approaches to neuroimaging will assist computer-aided analysis of neurological diseases. Feature extraction of neuroimages carried out using Artificial Neural Networks leads to better diagnoses. In this study, all the brain diseases are revisited to consolidate the methodologies carried out by various authors in the literature.
Keywords: Brain, Classification, Feature Extraction, Neural Network.
Scope of the Article: Design and Diagnosis