• MAYUR BHATI
• SWATI SHARMA

Image Segmentation is the area of image processing that has been identified as the key problem of medical image analysis and remains a popular and challenging area of research. The segmentation refers to the process of partitioning a digital image into multiple segments. The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is typically used to locate objects and boundaries in images. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain visual characteristics. In this Paper two types of approach for segmentation is done and compared. Firstly a brain MRI is taken and its noises are removed using filters and also by using wavelet denoising and after that the skull is stripped using the morphological operations like erosion, dilation. Then in the next approach the skull stripping using Brain Extraction tool (BET) and then applied K-means Clustering algorithm and then find out the % area segmented. Magnetic Resonance (MR) has become the main modality for brain imaging that facilitates safe, non-invasive assessment and monitoring of patients with neurodegenerative diseases

Segmentation. Skull stripping, K-means clustering, Fuzzy C-means clustering

"Evaluation of Skull Stripping in Magnetic Resonance Imaging using K-mean Clustering ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.324-332, June-2019, Available :http://www.jetir.org/papers/JETIR1907044.pdf

"Evaluation of Skull Stripping in Magnetic Resonance Imaging using K-mean Clustering ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp324-332, June-2019, Available at : http://www.jetir.org/papers/JETIR1907044.pdf