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[null,"1.","Record Nr.",null,"UNINA9910346767303321"]
[null,null,"Autore",null,"Stegmaier Johannes"]
[null,null,"Titolo",null,"New Methods to Improve Large-Scale Microscopy Image Analysis with Prior Knowledge and Uncertainty"]
[null,null,"Pubbl/distr/stampa",null,"KIT Scientific Publishing, 2017"]
[null,null,"ISBN",null,"1000060221"]
[null,null,"Descrizione fisica",null,"1 online resource (XII, 243 p. p.)"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","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."]