• Komal Vyas
• Dr. R. Jegadeesan
• K. Krishna Chaitanya Rao
• Sathvik Thogaru

Machine learning (ML) has gained enormous application with innovation in hardware requirements for computing. The application of computer vision techniques in health care has one of the aim to reduce human judgment in diagnosis. Thus, human error in judgment may be reduced. One of the primary diagnostic and treatment evaluation tools for interpretation has been magnetic resonance imaging (MRI). In fact MRI characteristics will help the doctor to avoid the human error in manual interpretation of medical content where the smallest aberrances in the human body can be identified. More preferred contrast information about brain tissues is provided by Magnetic Resonance imaging (MRI). MR images can also be used to determine normal and abnormal types of brain. Brain related diagnosis demands at most care and a minute error in judgment may be disastrous. This makes medical imaging very important field. Various imaging methods like CT Scans, X-Ray, and MRI are available but MRI is the most reliable and safe. In fact medical image segmentation is a complex and challenging task due to the intrinsic nature of the images which involves separating the tumor and organisms out of the medical data. Brain tumor segmentation from Magnetic Resonance Imaging (MRI) scans has an important role in the early tumor diagnosis and radiotherapy planning. In the proposed paper we evaluate using Particle Swam Optimization algorithm of medical image segmentation.

MRI, Image Segmentation, Particle Swarm Optimization, Principal component Analysis.

" A SURVEY ON BRAIN IMAGE SEGMENTATION USING PARTICLE SWARM OPTIMIZATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.65-70, March-2019, Available :http://www.jetir.org/papers/JETIRAU06010.pdf

" A SURVEY ON BRAIN IMAGE SEGMENTATION USING PARTICLE SWARM OPTIMIZATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp65-70, March-2019, Available at : http://www.jetir.org/papers/JETIRAU06010.pdf