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Proceedings Paper

Merging Of Different Segmentation Techniques For Cell Image Recognition
Author(s): Sebastiano B. Serpico; Gianni Vernazza; Silvana Dellepiane
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Paper Abstract

In this paper, we present a knowledge-based system for segmentation and interpretation of 2-D images, specialized for neural cells recognition, and based on both region and edge information. Cell images are obtained by acoustic microscopy, and are characterized by nonuniform background, and low contrast (expecially for dendrite contours). Neural cells have compact shapes, while dendrites are thin and elongated. Consequently, for cell bodies, region information has proved basic, while edges are used to refine their contours, or to solve incorrect situations. Edges are of major importance for dendrite location, since their shape creates some difficulties to region-based segmentation. Elementary regions are provided by region-growing; edges are obtained by detecting zero-crossings of the second derivative of grey-level behaviour. A symbolic representation of the above primitives is stored inside a Global Database (GDB), and contains information about properties and relations of regions and edges. Procedural knowledge, represented as production rules, and organized at hierarchical levels, is applied by means of a rule interpreter, according to the current problem status stored inside the GDB. As starting point, a region preclassification is performed on the basis of a priori knowledge about neuron and dendrite features; a refinement is subsequently obtained by employing alternatively edges and regions again. The system output is a symbolic map which shows background, cell bodies and dendrites in different colours. Experimental results are presented and discussed.

Paper Details

Date Published: 2 March 1989
PDF: 6 pages
Proc. SPIE 1027, Image Processing II, (2 March 1989); doi: 10.1117/12.950283
Show Author Affiliations
Sebastiano B. Serpico, Univ. of Genoa (Italy)
Gianni Vernazza, Univ. of Genoa (Italy)
Silvana Dellepiane, Univ. of Genoa (Italy)

Published in SPIE Proceedings Vol. 1027:
Image Processing II
Peter J.S. Hutzler; Andre J. Oosterlinck, Editor(s)

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