• MAYUR BHATI
• SWATI SHARMA

MRI (Magnet Resonance Image) is a scan used for a medical imaging procedure. In medical image processing medical images are corrupted by different types of noises & no proper techniques are there for skull stripping, segmentation and clustering in a single step. It is very important to obtain precise image to facilitate accurate observation for the given application. Removing of noise from medical image is now a very challenging issue in the field of medical image processing. To solve the above problem proposed a simple method which does noise reduction, morphological skull stripping, Brain segmentation and also Clustering at the last find the % area segmented. All these combined together will be beneficial both for Radiologist as well as patient. 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 Fuzzy C-Mean clustering algorithm. Now compare which result is good in the both clustering, the Fuzzy C-Mean clustering is best for this process so now for the % area segmentation used Fuzzy C- Mean clustering image. Magnetic Resonance (MR) has become the main modality for brain imaging that facilitates safe, non-invasive assessment and monitoring of patients with neurodegenerative diseases.

"Study and Evaluation of Skull Stripping in Magnetic Resonance Imaging Using Various Algorithms and Their Comparison", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.314-323, June-2019, Available :http://www.jetir.org/papers/JETIR1907043.pdf

"Study and Evaluation of Skull Stripping in Magnetic Resonance Imaging Using Various Algorithms and Their Comparison", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp314-323, June-2019, Available at : http://www.jetir.org/papers/JETIR1907043.pdf