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Proceedings Paper

Automatic object selection in computer-assisted microscopy
Author(s): Thierry Leloup; Nadine Lasudry; Robert Kiss; Philippe Van Ham
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Paper Abstract

The characterization of tumor aggressiveness is a very important step in cancer diagnosis and treatment. This can be achieved by examining the cells nuclei of the tissue. In order to perform a statistical study on a population of such nuclei, we have to characterize nuclei one by one. The problem is that the nuclei often appear in clusters and that other elements (totally unrepresentative of the studied tissue) can be present on the image. Moreover, we have to discard nuclei which do not guarantee valid data (broken nuclei, folded nuclei...). The purpose of our work is to separate clusters of nuclei into single-cell nuclei and eliminate undesirable elements of the image. Until now, this task was made by hand and was extremely slow and repetitive. Moreover, it implied a subjective basis, depending on the human operator. The method we developed is totally automatic. It is based on the elaboration of a binary mask containing objects which will be examined separately. Our algorithm has been tested on a large set of images coming from different tissues and the results are compared with the same task performed by human operators.

Paper Details

Date Published: 24 June 1998
PDF: 11 pages
Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); doi: 10.1117/12.310842
Show Author Affiliations
Thierry Leloup, Univ. of Brussels (Belgium)
Nadine Lasudry, Univ. of Brussels (Belgium)
Robert Kiss, Univ. of Brussels (Belgium)
Philippe Van Ham, Univ. of Brussels (Belgium)

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

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