Bilateral Filtering Allied with Neural Network Based on GLSZM Characteristic Mining and Typical Classification of Human Brain Images
S Hariharasudhan1, B Raghu2
1S.Hariharasudhan, Research Scholar/CSE, Bharath Institute of Higher Education and Research, Chennai, (Tamil Nadu), India.
2B.Raghu, Professor & Principal, SVS Groups of Institutions, Warangal, (Telangana), India.
Manuscript received on 23 March 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 March 2019 | PP: 665-669 | Volume-7 Issue-6, March 2019 | Retrieval Number: F2751037619/19©BEIESP
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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 article proposes an automatic classification support system to perceive the brain tumor and categorize the human brain images utilizing neural network allied with bilateral filter for medical relevant application. Hands-on medical image has perverted into a self-motivated exploration and investigative analysis is done in the region of Image processing. Noise expulsion in MRI (Magnetic Resonance Image) medical image is important and decisive for a extensive collection of handling image process presentations. In this research article, the proposed method consists of pre-processing and post processing technique using with the neural network allied with bilateral filtering and segmenting to eradicate the noise and GLSZM congregation algorithm segments and categorize the human brain images by countenancing for longitudinal information in sequence and also hypothesis preliminary association matrix unsystematically. The outcomes will be accessible as segmented medical image descriptions and classification takes place by means of neural network algorithm.
Keywords: Neural Network, bilateral filter, Image processing
Scope of the Article: Classification