Automatic Cell Image Segmentation Using a Shape-Classification Model
نویسنده
چکیده
This paper presents a segmentation method for detecting cells in immunohistochemically stained cytological images. A two-phase approach to segmentation is used where an unsupervised clustering approach coupled with cluster merging based on a fitness function is used as the first phase to obtain a first approximation of the cell locations. A joint segmentation-classification approach incorporating ellipse as a shape model is used as the second phase to detect the final cell contour. Results of segmentation are presented and compared to ground truth measurements.
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تاریخ انتشار 2007