ABC Based Neural Network Method for Brain Tumor Identification from MRI and CT Images
Mitha Rachel Jose1, J. Amar Pratap Singh2
1Mitha Rachel Jose, Research Scholar, Noorul Islam University, Tamil Nadu, India.
2J. Amar Pratap Singh, Professor and Director (Admin), Noorul Islam University, Tamil Nadu, India.
Manuscript received on November 20, 2019. | Revised Manuscript received on November 26, 2019. | Manuscript published on 30 November, 2019. | PP: 3506-3515 | Volume-8 Issue-4, November 2019. | Retrieval Number: D7677118419/2019©BEIESP | DOI: 10.35940/ijrte.D7677.118419
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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: According to the inconsistency and complication of tumors, MRI is a complicated method for categorizing brain tumor. Generally, the classification accuracy is enhanced by the help of pre-processing and feature extraction processes which are essential methods. In this document, we enhanced a brain tumor recognition process through ABC-ANN procedure. The anticipated procedure contains three segments such as Preprocessing, feature extraction and classification. Initially, the median filter and Histogram Equalization methods are used to augment the images. The second and third segments are FFT related attribute extraction and categorized by means of ABC related ANN method simultaneously.
Keywords: FFT-Fast Fourier Transform; ANN-Artificial Neural Network; ABC-Artificial Bee Colony Algorithm; HE-Histogram Equalization.
Scope of the Article: Healthcare Informatics.