Object Oriented Cell Image Segmentation

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Abstract
A correct segmentation of cell images into nucleus, cytoplasm and background is a prerequi-site for a working automatic pre-screening device for cervical cytology. This paper presents an algorithm for determining the segmentation thresholds. It is based on a-priori assumptions about a cell's shape and size and works on one object at a time, disregarding everything else in the image. The algorithm is capable of verifying that the isolated object really looks like a cell; an essential feature in an automatic system. The nucleus and cytoplasm thresholds are decided upon almost independently of each other. The algorithm works by tracking iso-density contours around the object to be isolated and its execution time is thus proportional to the length of the contour rather than the area of the image. Some preliminary results are given and the possibility of efficiently implementing the algorithm in hardware is discussed.

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