Model-based segmentation and quantification of fluorescent bacteria in 3D microscopy live cell images

Stefan Wörz; Constantin Kappel; Roland Eils; Karl Rohr

doi:10.1117/12.709825

26 March 2007 Model-based segmentation and quantification of fluorescent bacteria in 3D microscopy live cell images

Stefan Wörz, Constantin Kappel, Roland Eils, Karl Rohr

Proceedings Volume 6512, Medical Imaging 2007: Image Processing; 651234 (2007) https://doi.org/10.1117/12.709825
Event: Medical Imaging, 2007, San Diego, CA, United States

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.

Citation Download Citation

Stefan Wörz, Constantin Kappel, Roland Eils, and Karl Rohr "Model-based segmentation and quantification of fluorescent bacteria in 3D microscopy live cell images", Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 651234 (26 March 2007); https://doi.org/10.1117/12.709825

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