Imagining the future of bioimage analysis
Modern biological research increasingly relies on image data as a primary source of information in unraveling the cellular and molecular mechanisms of life. The quantity and complexity of the data generated by state-of-the-art microscopes preclude visual or manual analysis and require advanced compu...
Gespeichert in:
| Hauptverfasser: | , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
7 December 2016
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| In: |
Nature biotechnology
Year: 2016, Jahrgang: 34, Heft: 12, Pages: 1250-1255 |
| ISSN: | 1546-1696 |
| DOI: | 10.1038/nbt.3722 |
| Online-Zugang: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1038/nbt.3722 Verlag, lizenzpflichtig, Volltext: https://www.nature.com/articles/nbt.3722 
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| Verfasserangaben: | Erik Meijering, Anne E Carpenter, Hanchuan Peng, Fred A Hamprecht & Jean-Christophe Olivo-Marin |
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| 520 | |a Modern biological research increasingly relies on image data as a primary source of information in unraveling the cellular and molecular mechanisms of life. The quantity and complexity of the data generated by state-of-the-art microscopes preclude visual or manual analysis and require advanced computational methods to fully explore the wealth of information. In addition to making bioimage analysis more efficient, objective, and reproducible, the use of computers improves the accuracy and sensitivity of the analyses and helps to reveal subtleties that may be unnoticeable to the human eye. Many methods and software tools have already been developed to this end, but there is still a long way to go before biologists can blindly trust automated measurements. Here, we summarize the current state of the art in bioimage analysis and provide a perspective on likely future developments. | ||
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