New Methods to Improve Large-Scale Microscopy Image Analysis with Prior Knowledge and Uncertainty
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(Sprache: Englisch)
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...
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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.
Klappentext zu „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 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.
Bibliographische Angaben
- Autor: Johannes Stegmaier
- 2017, 266 Seiten, mit Abbildungen, Masse: 17 x 24 cm, Kartoniert (TB), Englisch
- Verlag: KIT Scientific Publishing
- ISBN-10: 3731505908
- ISBN-13: 9783731505907
Sprache:
Englisch
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