Software for bead-based registration of selective plane illumination microscopy data

By Stephan Preibisch, Stephan Saalfeld, Johannes E. Schindelin, Pavel Tomancak. Nature Methods, 2010

394 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Biophysics

View Paper: https://www.semanticscholar.org/paper/560b99553496308fdad4e750728517ad12414d5c

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Citations in the corpus

Biological Imaging Software Tools (2012, methodology): “The issue of interoperability is crucial for long-term progress in bioimage informatics, and general software libraries are one mechanism to achieve maximum integration among diverse platforms geared toward particular use cases (for example, software designed for automated processing of hundreds of ”
Fiji - an Open Source platform for biological image analysis (2012, methodology): “After acquisition, the multiview data can be reconstructed into a continuous 3D volume using fluorescent beads in the rigid agarose medium as fiduciary markers (bead-based SPIM Registration plugin 26 ).”
ImageJ2: ImageJ for the next generation of scientific image data (2017, methodology): “References for plugins shown: TrackMate [67], MaMuT [150], Multiview Reconstruction [70, 71], MotherMachine Analyzer (MoMA) [151, 152], Sholl Analysis [74], Kymograph Builder [153], Z-Spacing Correction [154], Trainable Weka Segmentation [155], Pendent Drop [156], SciView [157], BigDataViewer [66], ”
The light-sheet microscopy revolution (2018, methodology): “is handled in the OpenSpim configuration has been described [48] and simple 3D reconstruction is now implemented as Fiji plugin to correlate multiview 3D images [49].”
Building quantitative, three dimensional atlases of gene expression and morphology at cellular resolution (2013, background): “52 Mounting the biological samples is complicated by the rotational symmetry required about the light sheet.”
The ImageJ ecosystem: Open‐source software for image visualization, processing, and analysis (2020, background): “15,16 20 As the prevalence of large multidimensional datasets continues to grow, the ability to manually take measurements not only becomes impractically time-consuming, but the sensitivity, accuracy, objectivity, and reproducibility of doing so can become greatly inhibited.”