• Ronak Rafiq
• Vikas Kumar

Abstract- Brain tumor segmentation aims to separate the different tumor tissues such as active cells, necrotic core, and edema from normal brain tissues of White Matter (WM), Gray Matter (GM), and Cerebrospinal Fluid (CSF). MRI based brain tumor segmentation studies are attracting more and more attention in recent years due to non-invasive imaging and good soft tissue contrast of Magnetic Resonance Imaging (MRI) images. With the development of almost two decades, the innovative approaches applying computer-aided techniques for segmenting brain tumor are becoming more and more mature and coming closer to routine clinical applications. The purpose of this paper is to provide a comprehensive overview for MRI-based brain tumor segmentation methods. Firstly, a brief introduction to brain tumors and imaging modalities of brain tumors is given. In thesis proposed convolution based optimization. These step wise step refine the segmentation and improve the classification parameter with the help of particle swarm optimization.

Keywords: Magnetic Resonance Imaging, Gray Matter, White Matter, Cerebrospinal Fluid.

"BRAIN IMAGES SEGMENTATION BY OPTIMIZING CLUSTERING OF CONVOLUTION BASED FEATURES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.65-74, June 2019, Available :http://www.jetir.org/papers/JETIR1906M07.pdf

"BRAIN IMAGES SEGMENTATION BY OPTIMIZING CLUSTERING OF CONVOLUTION BASED FEATURES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp65-74, June 2019, Available at : http://www.jetir.org/papers/JETIR1906M07.pdf