Fuzzy Bio-Image Segmentation with Spatial Covariance

Tuan D. Pham

Image segmentation is an important research area in image analysis and its applications to medical and biological imaging. In particular, effective segmentation methods play an essential role in the analysis, classification, and quantification of bioimages for prognosis and preventive treatment. Different segmentation methods based on different criteria of optimality often give different results. This paper introduces a new strategy for modeling image spatial information in the setting of the fuzzy c-means algorithm for segmenting bio-images that are inherently fuzzy. The experimental results have shown the superior performance of the new method over some popular models for the segmentation of cell puncta.

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