TY - EJOUR
AU - Ghasemi, Jamal
AU - Mollaei, Mohammad Reza Karami
AU - Ghaderi, Reza
AU - Hojjatoleslami, Ali
PY - 2024
DA - February
TI - Multi-Dimensional Fuzzy C-Mean Considering Spatial Information for Brain MRI Segmentation
T2 - Majlesi Journal of Electrical Engineering
VL - 8
L1 - https://oiccpress.com/Majlesi-Journal-of-Electrical-Engineering/article/multi-dimensional-fuzzy-c-mean-considering-spatial-information-for-brain-mri-segmentation/
N2 - 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 .
IS - 1
PB - OICC Press
KW - Segmentation, Brain MRI, Fuzzy c-mean 
EN -