Segmentation of Brain Tumor using Hybrid Approach of Fast Bounding Box and Thresholding in MRI
V Ramakrishna Sajja1, Sajja Radha Rani2, D.S Bhupal Naik3, K Pratyusha4
1V Ramakrishna Sajja, Department of Computer Science and Engineering, VFSTR deemed to be University, Vadlamudi, Guntur (Andhra Pradesh), India.
2Sajja Radha Rani, Department of Computer Science and Engineering, VFSTR deemed to be University, Vadlamudi, Guntur (Andhra Pradesh), India.
3DS Bhupal Naik, Department of Computer Science and Engineering, VFSTR deemed to be University, Vadlamudi, Guntur (Andhra Pradesh), India.
4Dr. K. Kalaiselvi, Department of Electronics and Communications Engineering, VFSTR deemed to be University, Vadlamudi, Guntur (Andhra Pradesh), India.
Manuscript received on 12 February 2019 | Revised Manuscript received on 02 March 2019 | Manuscript Published on 08 June 2019 | PP: 118-123 | Volume-7 Issue-5S4, February 2019 | Retrieval Number: E10230275S419/19©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: Brain tumor is a deadly sickness and proliferate its cells in an uncontrolled way where it cannot be confidently detected without MRI. MRI image technique provides more accurate results than CT, Ultrasound and X-ray clinical methods. As we realize that Brain tumor is the most hazardous thus its identification ought to be quick and more precise. This can be achieved by processing of automated tumor detection methods on MRI brain images. Noise and delay for detection of tumor will affect the image accuracy. Here we proposed an automatic detection method to easily separate tumor and nontumor parts of the brain. Anisotropic Diffusion filter applied to eliminate noise information and artifacts from the input brain MRI. Fast Bounding Box (FBB) and Threshold methodologies have been employed for segmentation of the brain tumor at image level of the brain.
Keywords: Image Segmentation, Anisotropic Diffusion Filter, Fast Bounding Box, Naïve Bayes Classifier.
Scope of the Article: Image Security