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Automation strategies for large-scale 3D image analysis

Automation strategies for large-scale 3D image analysis Abstract New imaging techniques enable visualizing and analyzing a multitude of unknown phenomena in many areas of science at high spatio-temporal resolution. The rapidly growing amount of image data, however, can hardly be analyzed manually and, thus, future research has to focus on automated image analysis methods that allow one to reliably extract the desired information from large-scale multidimensional image data. Starting with infrastructural challenges, we present new software tools, validation benchmarks and processing strategies that help coping with large-scale image data. The presented methods are illustrated on typical problems observed in developmental biology that can be answered, e.g., by using time-resolved 3D microscopy images. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png at - Automatisierungstechnik de Gruyter

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Publisher
de Gruyter
Copyright
Copyright © 2016 by the
ISSN
0178-2312
eISSN
2196-677X
DOI
10.1515/auto-2016-0019
Publisher site
See Article on Publisher Site

Abstract

Abstract New imaging techniques enable visualizing and analyzing a multitude of unknown phenomena in many areas of science at high spatio-temporal resolution. The rapidly growing amount of image data, however, can hardly be analyzed manually and, thus, future research has to focus on automated image analysis methods that allow one to reliably extract the desired information from large-scale multidimensional image data. Starting with infrastructural challenges, we present new software tools, validation benchmarks and processing strategies that help coping with large-scale image data. The presented methods are illustrated on typical problems observed in developmental biology that can be answered, e.g., by using time-resolved 3D microscopy images.

Journal

at - Automatisierungstechnikde Gruyter

Published: Jul 28, 2016

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