New Methods to Improve Large-Scale Microscopy Image Analysis with Prior Knowledge and Uncertainty
Multidimensional imaging techniques provide powerful ways to examine various kinds of scientific questions. The routinely produced data sets in the terabyte-range, however, can hardly be analyzed manually and require an extensive use of automated image analysis. The present work introduces a new con...
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| Format: | Electronic Book Chapter |
| Language: | English |
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KIT Scientific Publishing
2017
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| Subjects: | |
| Online Access: | DOAB: download the publication DOAB: description of the publication |
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| 020 | |a 9783731505907 | ||
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| 024 | 7 | |a 10.5445/KSP/1000060221 |c doi | |
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| 042 | |a dc | ||
| 100 | 1 | |a Stegmaier, Johannes |4 auth | |
| 245 | 1 | 0 | |a New Methods to Improve Large-Scale Microscopy Image Analysis with Prior Knowledge and Uncertainty |
| 260 | |b KIT Scientific Publishing |c 2017 | ||
| 300 | |a 1 electronic resource (XII, 243 p. p.) | ||
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| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a Multidimensional imaging techniques provide powerful ways to examine various kinds of scientific questions. The routinely produced data sets in the terabyte-range, however, can hardly be analyzed manually and require an extensive use of automated image analysis. The present work introduces a new concept for the estimation and propagation of uncertainty involved in image analysis operators and new segmentation algorithms that are suitable for terabyte-scale analyses of 3D+t microscopy images. | ||
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| 546 | |a English | ||
| 653 | |a 3D Bildanalyse | ||
| 653 | |a Algorithms | ||
| 653 | |a Software3D Image Analysis | ||
| 653 | |a Algorithmen | ||
| 653 | |a Data Mining | ||
| 653 | |a Entwicklungsbiologie | ||
| 653 | |a Software | ||
| 653 | |a Developmental Biology | ||
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| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/54603 |7 0 |z DOAB: description of the publication |