title: Fast globally optimal segmentation of cells in fluorescence microscopy images.
abstract: Accurate and efficient segmentation of cells in fluorescence microscopy images is of central importance for the quantification of protein expression in high-throughput screening applications. We propose a new approach for segmenting cell nuclei which is based on active contours and convex energy functionals. Compared to previous work, our approach determines the global solution. Thus, the approach does not suffer from local minima and the segmentation result does not depend on the initialization. We also suggest a numeric approach for efficiently computing the solution. The performance of our approach has been evaluated using fluorescence microscopy images of different cell types. We have also performed a quantitative comparison with previous segmentation approaches.
authors: University of Heidelberg, BIOQUANT, IPMB, and DKFZ Heidelberg, Dept. Bioinformatics and Functional Genomics, Biomedical Computer Vision Group.
authors: Jan-Philip
authors: JP
authors: Bergeest
authors: Karl
authors: K
authors: Rohr
mesh_terms: D000465:Algorithms; D000818:Animals; D003585:Cell Biology; D002467:Cell Nucleus / Q000378:metabolism*; D003952:Diagnostic Imaging / Q000379:methods; D005456:Fluorescent Dyes / Q000494:pharmacology; D007091:Image Processing, Computer-Assisted; D051379:Mice; D008856:Microscopy, Fluorescence / Q000379:methods*; D015233:Models, Statistical; D008962:Models, Theoretical; D041681:NIH 3T3 Cells; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results
chemical_list: D005456:Fluorescent Dyes