Fully automatic segmentation of nuclei in a zebrafish embryo (image data: Oates lab, MPI-CBG). Nuclei with different brightness (A, B) are correctly segmented and touching nuclei are not fused (C) .
Segmenting 3D cell shapes from a drosophila wing disc (image data: Basler lab, University of Zurich) using a membrane stain only, and reconstructing the cell-packing graph.
Simulation of growth and morphogenesis as driven by a reaction-diffusion system on a deforming surface. The surface deformation is driven by the local concentration (joint work with Michael Bergdorf and Petros Koumoutsakos, ETH Zurich) .
3D reconstruction of the endoplasmic reticulum of a VERO cell (image data: Helenius lab, ETH Zurich) [3,4].
The parallel particle mesh library (PPM) is a software middleware for high-performance particle simulations on computer clusters and supercomputers . It has enabled several state-of-the-art simulations that have outperformed handwritten codes . PPM is the basis for most software developed in our group.
Automatic detection and segmentation of the cell outline of a polarizing and migrating keratocyte from phase-contrast images (image data: Verkhovsky lab, EPFL Lausanne) .
Simulation of fluorescence recovery after photobleaching in the endoplasmic reticulum. The spatiotemporal evolution of GFP concentration is simulated using a continuum particle method [3,4].
Deconvolving active contours segment the outlines of small, intra-cellular objects while correcting for the point-spread function of the microscope . This enables localization precisions in the nanometer range .
 J. Cardinale, G. Paul, and I. F. Sbalzarini. Discrete region competition for unknown numbers of connected regions. IEEE Trans. Image Process., 2012.
 M. Bergdorf, I. F. Sbalzarini, and P. Koumoutsakos. A Lagrangian particle method for reaction-diffusion systems on deforming surfaces. J. Math. Biol., 61:649–663, 2010.
 I. F. Sbalzarini, A. Mezzacasa, A. Helenius, and P. Koumoutsakos. Effects of organelle shape on fluorescence recovery after photobleaching. Biophys. J., 89(3):1482–1492, 2005.
 I. F. Sbalzarini, A. Hayer, A. Helenius, and P. Koumoutsakos. Simulations of (an)isotropic diffusion on curved biological surfaces. Biophys. J., 90(3):878–885, 2006.
 I. F. Sbalzarini, J. H. Walther, M. Bergdorf, S. E. Hieber, E. M. Kotsalis, and P. Koumoutsakos. PPM – a highly efficient parallel particle-mesh library for the simulation of continuum systems. J. Comput. Phys., 215(2):566–588, 2006.
 I. F. Sbalzarini. Abstractions and middleware for petascale computing and beyond. Intl. J. Distr. Systems & Technol., 1(2):40–56, 2010.
 M. E. Ambühl, C. Brepsant, J.-J. Meister, A. B. Verkhovsky, and I. F. Sbalzarini. High-resolution cell outline segmentation and tracking from phase-contrast microscopy images. J. Microsc., 245(2):161–170, 2012.
 J. A. Helmuth, C. J. Burckhardt, U. F. Greber, and I. F. Sbalzarini. Shape reconstruction of subcellular structures from live cell fluorescence microscopy images. J. Struct. Biol., 167:1–10, 2009.
 J. A. Helmuth and I. F. Sbalzarini. Deconvolving active contours for fluorescence microscopy images. In Proc. Intl. Symp. Visual Computing (ISVC), volume 5875 of Lecture Notes in Computer Science, pages 544–553, Las Vegas, USA, November 2009. Springer.