<< back

Publication Details

Reference Category Book chapters
DOI / URL link
Title (Primary) Segmenting microorganisms in multi-modal volumetric datasets using a modified watershed transform
Title (Secondary) Pattern Recognition. 24th DAGM Symposium Zurich, Switzerland, September 16–18, 2002 Proceedings
Author Bergner, S.; Pohle, R.; Al Zubi, S.; Tönnis, K.; Eitner, A.; Neu, T.R.;
Publisher Van Gool, L.;
Journal Lecture Notes in Computer Science
Year 2002
Department FLOEK; GM;
Volume 2449
Language englisch;
Abstract

Aquatic interfaces in the environment are colonized by a large variety of pro- and eucaryotic microorganisms, which may be examined by confocal laser scanning microscopy. We describe an algorithm to identify and count the organisms in multi-channel volumetric datasets. Our approach is an intermediate-level segmentation combining a voxel-based classification with low-level shape characteristics (convexity). Local intensity maxima are used as seed points for a watershed transform. Subsequently, we solve the problem of over-segmentation by merging regions. The merge criterion is taking the depth of the ‘valley’ between adjacent segments into account. The method allows to make correct segmentation decisions without the use of additional shape information. Also this method provides a good basis for further analysis steps, e.g. to recognize organisms that consist of multiple parts.
ID 5354
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=5354
Bergner, S., Pohle, R., Al Zubi, S., Tönnis, K., Eitner, A., Neu, T.R. (2002):
Segmenting microorganisms in multi-modal volumetric datasets using a modified watershed transform
In: Van Gool, L. (ed.)
Pattern Recognition. 24th DAGM Symposium Zurich, Switzerland, September 16–18, 2002 Proceedings
Lect. Notes Comput. Sci. 2449
Springer, Berlin, Heidelberg, New York, p. 429 - 437