PUBLICATION

Fast segmentation of stained nuclei in terabyte-scale, time resolved 3D microscopy image stacks

Authors
Stegmaier, J., Otte, J.C., Kobitski, A., Bartschat, A., Garcia, A., Nienhaus, G.U., Strähle, U., Mikut, R.
ID
ZDB-PUB-140513-433
Date
2014
Source
PLoS One   9: e90036 (Journal)
Registered Authors
Mikut, Ralf, Otte, Jens, Strähle, Uwe
Keywords
none
MeSH Terms
  • Algorithms
  • Cell Nucleus*
  • Image Processing, Computer-Assisted*
  • Imaging, Three-Dimensional*
  • Microscopy/methods*
  • Microscopy, Fluorescence/methods
  • Reproducibility of Results
PubMed
24587204 Full text @ PLoS One
Abstract

Automated analysis of multi-dimensional microscopy images has become an integral part of modern research in life science. Most available algorithms that provide sufficient segmentation quality, however, are infeasible for a large amount of data due to their high complexity. In this contribution we present a fast parallelized segmentation method that is especially suited for the extraction of stained nuclei from microscopy images, e.g., of developing zebrafish embryos. The idea is to transform the input image based on gradient and normal directions in the proximity of detected seed points such that it can be handled by straightforward global thresholding like Otsu’s method. We evaluate the quality of the obtained segmentation results on a set of real and simulated benchmark images in 2D and 3D and show the algorithm’s superior performance compared to other state-of-the-art algorithms. We achieve an up to ten-fold decrease in processing times, allowing us to process large data sets while still providing reasonable segmentation results.

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