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Proceedings Paper

Model-based segmentation and quantification of fluorescent bacteria in 3D microscopy live cell images
Author(s): Stefan Wörz; Constantin Kappel; Roland Eils; Karl Rohr
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Paper Abstract

We introduce a new model-based approach for segmenting and quantifying fluorescent bacteria in 3D microscopy live cell images. The approach is based on a new 3D superellipsoidal parametric intensity model, which is directly fitted to the image intensities within 3D regions-of-interest. Based on the fitting results, we can directly compute the total amount of intensity (fluorescence) of each cell. In addition, we introduce a method for automatic initialization of the model parameters, and we propose a method for simultaneously fitting clustered cells by using a superposition of 3D superellipsoids for model fitting. We demonstrate the applicability of our approach based on 3D synthetic and real 3D microscopy images.

Paper Details

Date Published: 26 March 2007
PDF: 10 pages
Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 651234 (26 March 2007); doi: 10.1117/12.709825
Show Author Affiliations
Stefan Wörz, Univ. of Heidelberg, IPMB (Germany)
German Cancer Research Ctr. Heidelberg (Germany)
Constantin Kappel, German Cancer Research Ctr. Heidelberg (Germany)
Roland Eils, Univ. of Heidelberg, IPMB (Germany)
German Cancer Research Ctr. Heidelberg (Germany)
Karl Rohr, Univ. of Heidelberg, IPMB (Germany)
German Cancer Research Ctr. Heidelberg (Germany)


Published in SPIE Proceedings Vol. 6512:
Medical Imaging 2007: Image Processing
Josien P. W. Pluim; Joseph M. Reinhardt, Editor(s)

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