International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 47 - Number 16 |
Year of Publication: 2012 |
Authors: Iraky Khalifa, Aliaa Youssif, Howida Youssry |
10.5120/7275-0446 |
Iraky Khalifa, Aliaa Youssif, Howida Youssry . MRI Brain Image Segmentation based on Wavelet and FCM Algorithm. International Journal of Computer Applications. 47, 16 ( June 2012), 32-39. DOI=10.5120/7275-0446
Image segmentation plays a preliminary and indispensable step in medical image processing. Magnetic resonance (MR) segmentation used for brain tissues extraction white matter (WM), gray matter (GM) and cerebrospinal fluids (CSF). These tissues help in many medical image segmentation applications such as radiotherapy planning, clinical diagnosis, treatment planning and Alzheimer disease. This paper presents a novel manipulation or utilization of Fuzzy C- Means (FCM) Clustering by using wavelet Decomposition for feature extraction and feature vector treat as input to FCM. This algorithm is called Wavelet Fuzzy C- means (WFCM), the algorithm results are compared with standard FCM and Kernelized Fuzzy C- Means (KFCM). The performance of the proposed segmentation algorithm provides satisfactory results compared with the other two algorithms.