Unsupervised Segmentation of Medical Image Based on FCM and Mutual Information

In the scope of medical image processing, segmentation is important and difficult. This paper presents a novel algorithm for segmentation of medical image. Our algorithm is formulated by combining the fuzzy c-means clustering (FCM) algorithm with the mutual information (MI) technique. The initial threshold can be chosen using FCM algorithm, and in the iteration process, an optimal threshold will be determined by maximizing the MI between the original volume and the thresholded volume. We evaluate the effectiveness of the proposed approach by applying it to the medical images, including magnetic resonance imaging (MRI), microphotographic image. The experimental results indicate that the proposed method has not only visually better or comparable segmentation effect but also, more favorably, removal ability for noise.

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