• Harinder Kaur
• Er.Ram Singh

In this paper a thorough review of various Magnetic Resonance Images (MRI) segmentation techniques is presented. MR image segmentation techniques are used in clinical establishment to diagnose various types of diseases. Segmentation of MRI is a challenging task. Automatic segmentation as compare to the manual segmentation of MRI is helpful to do the segmentation easily and in less time to extract an interested area from an image. Segmentation of brain MRI is the significance for diagnosis brain disease. Various segmentation techniques are available which are used to segment an MR image like Thresholding, clustering, region growing, watershed algorithms, machine learning, deep learning and neural networks, etc. Each and every segmentation technique has its own advantages, and limitations. These segmentation techniques provide us an efficient approach to segment the brain MRI for detect the brain tumor.

Magnetic resonance images, Brain tumor, Image segmentation, Image segmentation techniques.

"Brain Magnetic Resonance Images Segmentation Techniques: A Review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.281-289, June 2019, Available :http://www.jetir.org/papers/JETIR1907929.pdf

"Brain Magnetic Resonance Images Segmentation Techniques: A Review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp281-289, June 2019, Available at : http://www.jetir.org/papers/JETIR1907929.pdf