Comparison of Segmentation Algorithms by A Mathematical Model For Resolving Islands and Gulfs in Nuclei of Cervical Cell Images

Cell segmentation from microscopic images is the first stage of the automatic biomedical image processing, which plays a crucial role in the study of cell behaviour which is a very difficult and tedious task because of the variation that exist in illumination and dye concentration of the cells due to the staining procedure. This paper proposes a new method for segmentation of cervical cell nuclei based on a simple mathematical model to eliminate and resolve islands and gulfs which appear in the segmented output of conventional thresholding and region growing methods of segmentation. These components are eliminated and resolved and added to their related cell regions by our proposed mathematical model which first detects the borders of those structures and if it lies within the associated region they are placed within that region. The performance was evaluated and compared with the above mentioned methods. A simple mathematical vision system model to segment and analyze cytological image nuclei is proposed.

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