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Proceedings Paper

Deformable membrane for the segmentation of cytological samples
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Paper Abstract

In clinical cytology quantitative parameters have to be extracted from a large number of biological samples to obtain diagnostically relevant and reproducible information. Computer-assisted microscopy can provide methods that increase the quality and comparability of clinical studies by reducing the subjective influence of human operators on their results. In order to guarantee the correctness of extracted parameters automatic and reliable segmentation of the samples is required. For the detection of cytological objects a novel deformable membrane model is presented which is strictly based on macroscopical mechanics and statics. This is appropriate for modeling physiological membranes, because their shape is determined exclusively by mechanical forces. The self-driven membrane converges iteratively towards a stable state, where the contrary forces are in balance. However, active contours may not yield sufficient detection quality for acquisition of quantitative parameters. Therefore, after convergence a stochastic optimization process corrects the contour according to local graylevel information. This yields a contour that is well- adapted to the local graylevel structure. Additionally, for subsequent cytometric quantifications a local measure of confidence is provided for the contour. this can be used to enhance the robustness of the extracted parameters by incorporating the confidence factors in the quantification process. The method is applied to cytological and histological samples of different magnification.

Paper Details

Date Published: 24 June 1998
PDF: 12 pages
Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); doi: 10.1117/12.310852
Show Author Affiliations
Volker H. Metzler, Aachen Univ. of Technology (Germany)
Joerg Bredno, Aachen Univ. of Technology (Germany)
Thomas Martin Lehmann, Aachen Univ. of Technology (Germany)
Klaus Spitzer, Aachen Univ. of Technology (Germany)


Published in SPIE Proceedings Vol. 3338:
Medical Imaging 1998: Image Processing
Kenneth M. Hanson, Editor(s)

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