Fast segmentation of stained nuclei in terabyte-scale, time resolved 3D microscopy image stacks.
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 p...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2014-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC3937404?pdf=render |
| _version_ | 1818983550326669312 |
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| author | Johannes Stegmaier Jens C Otte Andrei Kobitski Andreas Bartschat Ariel Garcia G Ulrich Nienhaus Uwe Strähle Ralf Mikut |
| author_facet | Johannes Stegmaier Jens C Otte Andrei Kobitski Andreas Bartschat Ariel Garcia G Ulrich Nienhaus Uwe Strähle Ralf Mikut |
| author_sort | Johannes Stegmaier |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-20T18:04:53Z |
| format | Article |
| id | doaj.art-2ba94cf77a784a468934eb4225519ff9 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-20T18:04:53Z |
| publishDate | 2014-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-2ba94cf77a784a468934eb4225519ff92022-12-21T19:30:34ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0192e9003610.1371/journal.pone.0090036Fast segmentation of stained nuclei in terabyte-scale, time resolved 3D microscopy image stacks.Johannes StegmaierJens C OtteAndrei KobitskiAndreas BartschatAriel GarciaG Ulrich NienhausUwe SträhleRalf MikutAutomated 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.http://europepmc.org/articles/PMC3937404?pdf=render |
| spellingShingle | Johannes Stegmaier Jens C Otte Andrei Kobitski Andreas Bartschat Ariel Garcia G Ulrich Nienhaus Uwe Strähle Ralf Mikut Fast segmentation of stained nuclei in terabyte-scale, time resolved 3D microscopy image stacks. PLoS ONE |
| title | Fast segmentation of stained nuclei in terabyte-scale, time resolved 3D microscopy image stacks. |
| title_full | Fast segmentation of stained nuclei in terabyte-scale, time resolved 3D microscopy image stacks. |
| title_fullStr | Fast segmentation of stained nuclei in terabyte-scale, time resolved 3D microscopy image stacks. |
| title_full_unstemmed | Fast segmentation of stained nuclei in terabyte-scale, time resolved 3D microscopy image stacks. |
| title_short | Fast segmentation of stained nuclei in terabyte-scale, time resolved 3D microscopy image stacks. |
| title_sort | fast segmentation of stained nuclei in terabyte scale time resolved 3d microscopy image stacks |
| url | http://europepmc.org/articles/PMC3937404?pdf=render |
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