OICC Press Majlesi Journal of Electrical Engineering 2345-3796 8 1 2024 02 21 Multi-Dimensional Fuzzy C-Mean Considering Spatial Information for Brain MRI Segmentation EN Jamal Ghasemi Faculty of Engineering & Technology, University of Mazandaran Mohammad Reza Karami Mollaei Department of Electrical and Computer, Babol University of Technology, Babol, Iran Reza Ghaderi Shahid Beheshti University, Tehran, Iran Ali Hojjatoleslami School of Computing, University of Kent, Canterbury, UK Journal Article 2024 02 21 Due to artifacts, brain magnetic resonance image (MRI) segmentation is a complicated concern. This research work presents an image segmentation approach for brain magnetic resonance (MR) images. The proposed method is based on multi dimensional fuzzy C-mean. In this technique, different features of neighbouring pixels such as mean, standard deviation and singular value are extracted and then a multi dimensional feature vector is created in feature selection stage in which the best combination of extracted features is used. The created feature vector is used as an input to the multi dimensional FCM. The results have been evaluated with manual segmentation on two publicly available datasets .