Edge detection based on Fuzzy C Means in medical image processing system

In the modern life, people often face a few dangerous diseases, the time is considered as gold. Therefore, the survival of patients depends on whether the doctor is right or wrong in diagnosis. While the edges of object in magnetic resonance image (MRI) are important clues, which can make doctors know the problems. In real life, medical images often have low quality, so to find the object boundaries in images is not an easy task. In this paper, a new approach to MRI edge detection issue is shown. Our proposed method includes three stages. Firstly, using the Semi Translation Invariant Contourlet Transform (STICT) to improve quality of the original MRI. Secondly, the result of first stage is subjected to image segmentation by using Fuzzy C Means (FCM) clustering method. Finally, Canny edge detection method is applied to detect the fine edges. The proposed method is better than the other recent methods based on compared results.