This thesis describes the development of an automated image segmentation system for resolving overlapping cell nuclei in crowded scenes such as tissue biopsy section images. The system uses a succession of imaging algorithms that combine to double the number of extracted nuclei from lung epithelial section images compared to selecting free lying nuclei. (1) The system uses the distance transform and watershed transformation to analyse the shape of object clusters and split them into smaller clusters or into individual nuclei. The watershed algorithm reliably separates two overlapping ellipses provided less than 30% of either ellipse's perimeter is occluded by the other. (2) A Hough transform algorithm was created by combining the ellipse center finding routine of Yuen with the least squares ellipse fitting formula of Fitzgibbon. Fitzgibbon's formula was adapted to include a weighting for data points so that strong ellipse edges contribute more in the determination of ellipse fit parameters. The transform was tested on a set of 431 overlapping nuclei in cytological images of lung tumour cell lines grown in culture. The Hough transform was able to produce good ellipse fits for 85% of the nuclei in the set. (3) Active contour refinement is used to refine the borders of objects segmented using the Hough transform. It was applied to the cytological image set and reduced the area misfit measure between the true nuclear mask and the Hough ellipse approximations from 8 +/- 4% to 4 +/- 2%. The final segmentation of the nuclei created borders that delineated the overlap regions between nuclear pairs. These overlap regions were then measured for cytological and histological images to determine if the mean optical density (OD) in non-overlap regions could be used to predict the mean OD in overlap regions. It was found that the overlap regions contain 60--70% of the predicted OD.; The complete segmentation system was used to automatically segment biopsy section images for the purpose of recovering intact nuclei for morphometric analysis. Experiments on a set of ten tissue section images revealed that an average of 55 free lying nuclear shaped objects can be extracted from typical section frames, 83 can be extracted by applying the watershed algorithm and 102 can be extracted using the complete segmentation system. (Abstract shortened by UMI.)
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