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Benjamin Schmid

Researcher at University of Erlangen-Nuremberg

Publications -  73
Citations -  48505

Benjamin Schmid is an academic researcher from University of Erlangen-Nuremberg. The author has contributed to research in topics: Induced pluripotent stem cell & Light sheet fluorescence microscopy. The author has an hindex of 23, co-authored 67 publications receiving 34884 citations. Previous affiliations of Benjamin Schmid include University of Würzburg & Max Planck Society.

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Fiji: an open-source platform for biological-image analysis

TL;DR: Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis that facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system.
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BoneJ: Free and extensible bone image analysis in ImageJ.

TL;DR: This work implemented standard bone measurements in a novel ImageJ plugin, BoneJ, with which it analysed trabecular bone, whole bones and osteocyte lacunae and found that available software solutions were expensive, inflexible or methodologically opaque.
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A high-level 3D visualization API for Java and ImageJ

TL;DR: This framework enriches the ImageJ software libraries with methods that greatly reduce the complexity of developing image analysis tools in an interactive 3D visualization environment and provides high-level access to volume rendering, volume editing, surface extraction, and image annotation.
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An integrated micro- and macroarchitectural analysis of the Drosophila brain by computer-assisted serial section electron microscopy.

TL;DR: This study applies the software package TrakEM2 to reconstruct neuronal microcircuitry from TEM sections of a small brain, the early larval brain of Drosophila melanogaster, and describes the network motifs most frequently encountered in the Drosophile neuropile.
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Rapid 3D light-sheet microscopy with a tunable lens.

TL;DR: This work has built a light-sheet microscope that uses remote focusing with an electrically tunable lens (ETL) and achieves flexible volume imaging at much higher speeds than previously reported.