Christian Tischer1,2,3, Ashis Ravindran4, Sabine Reither2,3, Nicolas Chiaruttini5, Rainer Pepperkok2,3, Nils Norlin3,6,7. 1. Centre for Bioimage Analysis, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany. 2. Advanced Light Microscopy Facility, EMBL, Heidelberg, Germany. 3. Cell Biology and Biophysics Unit, EMBL, Heidelberg, Germany. 4. University of Heidelberg, Germany. 5. BioImaging & Optics Platform (BIOP), Faculty of Life Sciences (SV), Ecole Polytechnique Fédérale de Lausanne, Switzerland. 6. Department of Experimental Medical Science, Lund University, Sweden. 7. Lund University Bioimaging Centre, Lund University, Sweden.
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).
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).
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