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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.
DETAILS
New Methods to Improve Large-Scale Microscopy Image Analysis with Prior Knowledge and Uncertainty
Dissertationsschrift
Stegmaier, Johannes
Kartoniert, 266 S.
graph. Darst.
Sprache: Englisch
24 cm
KIT Scientific Publishing (2017)
Gewicht: 640 g
ISBN-13: 978-3-7315-0590-7
Titelnr.: 62399632