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ABSTRACT: Summary
Modern bioimaging and related areas such as sensor technology have undergone tremendous development over the last few years. As a result, contemporary imaging techniques, particularly electron microscopy (EM) and light sheet microscopy, can frequently generate datasets attaining sizes of several terabytes (TB). As a consequence, even seemingly simple data operations such as cropping, chromatic- and drift-corrections and even visualisation, poses challenges when applied to thousands of time points or tiles. To address this we developed BigDataProcessor2-a Fiji plugin facilitating processing workflows for TB sized image datasets.Availability and implementation
BigDataProcessor2 is available as a Fiji plugin via the BigDataProcessor update site. The application is implemented in Java and the code is publicly available on GitHub (https://github.com/bigdataprocessor/bigdataprocessor2).
SUBMITTER: Tischer C
PROVIDER: S-EPMC8479660 | biostudies-literature | 2021 Feb
REPOSITORIES: biostudies-literature
Tischer Christian C Ravindran Ashis A Reither Sabine S Chiaruttini Nicolas N Pepperkok Rainer R Norlin Nils N
Bioinformatics (Oxford, England) 20210901 18
<h4>Summary</h4>Modern bioimaging and related areas such as sensor technology have undergone tremendous development over the last few years. As a result, contemporary imaging techniques, particularly electron microscopy (EM) and light sheet microscopy, can frequently generate datasets attaining sizes of several terabytes (TB). As a consequence, even seemingly simple data operations such as cropping, chromatic- and drift-corrections and even visualisation, poses challenges when applied to thousan ...[more]