• Dodt, Hans Ulrich
• Pende, Marko
• Hahn, Christian
• Becker, Klaus
• Saghafi, Saiedeh

Abstract

<jats:title>Abstract</jats:title><jats:p>We developed an open‐source deconvolution software that stunningly increases the visibility of minute details, as for example, neurons or nerve fibers in light‐sheet microscopy or confocal microscopy data by combining rolling ball background subtraction in three directions with deconvolution using a synthetic or measured point spread function. Via automatic block‐wise processing image stacks of virtually unlimited size can be deconvolved even on small computers with 8 or 16 GB RAM. By parallelization and optional GPU‐acceleration, the software works with high speed: On a PC equipped with a state‐of‐the‐art NVidia graphic board a three dimensional (3D)‐stack of about 1 billion voxels can be deconvolved within 5 to 10 minutes. The implemented variation of the Richardson‐Lucy deconvolution algorithm preserves the photogrammetry of the image data by using flux‐preserving regularization, an approach that to our knowledge has not been applied for deconvolving microscopy data before.<jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/jbio202100290-gra-0001.png" xlink:title="image" /></jats:p>

Topics

• confocal microscopy