6 Tiles, 1 channel, 261MB
6 Tiles, 1 channel, 132MB
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The goal of XuvTools is to provide tools, that combine multiple microscopic recordings to obtain a larger field of view ("stitching") and a higher dynamic range ("HDR" recombination), or better resolution (multi view reconstruction), and to make these tools publicly available.
Current biomedical research increasingly requires imaging large and thick 3D structures at high resolution. Prominent examples are the tracking of fine filaments over long distances in brain slices, or the localization of gene expression or cell migration in whole animals like Caenorhabditis elegans or zebrafish. To obtain both high resolution and a large field of view (FOV), a combination of multiple recordings ("tiles") is one of the options. Although hardware solutions exist for fast and reproducible acquisition of multiple 3D tiles, generic software solutions are missing to assemble ("stitch") these tiles quickly and accurately.
In this paper we present a framework that achieves fully automated
recombination of tiles recorded at arbitrary positions in 3D space,
as long as some small overlap between tiles is provided. A fully
automated 3D correlation between all tiles is achieved such that
no manual interaction or prior knowledge about tile positions is
needed.
We use (1) phase-only correlation in a multi scale approach to
estimate the coarse positions, (2) normalized cross-correlation of
small patches extracted at salient points to obtain the precise
matches, (3) find the globally optimal placement for all tiles by a
singular value decomposition, and (4) accomplish a nearly seamless
stitching by a bleaching correction at the tile borders. If the
dataset contains multiple channels, all channels are used to obtain
the best matches between tiles. For speedup we employ a heuristic
method to prune unneeded correlations, and compute all correlations
via the fast Fourier transform ("FFT"), thereby achieving very good
runtime performance.
We demonstrate the successful application of the proposed framework to a wide range of different datasets from whole zebrafish embryos and C. elegans, mouse and rat brain slices and fine plant hairs (trichome). Further, we compare our stitching results to those of other commercially and freely available software solutions.
The algorithms presented are being made available freely as an open source toolset "XuvTools" at the corresponding authors website licensed under the GNU General Public License (GPL) v2. Binaries are provided for Linux and Microsoft Windows. The toolset is written in templated C++, such that it can operate on datasets with any bit-depth. Due to the consequent use of 64bit addressing, stacks of arbitrary size (i.e. larger than 4GB) can be stitched. The runtime on a standard desktop computer is typically in the range of a few minutes.
XuvTools is developed in a cooperation of three scientific institutes, all located around the beautiful Baden in southwestern Germany. Namely, the institutes are from the Albert-Ludwigs-University Freiburg, Germany, the Chair of Pattern Recognition and Image Processing (LMB) of the Institute for Computer Science, the Developmental Biology Unit (Developmental Biology) of the Department of Biology I, and the Life Imaging Center of the 'Zentrum für Biosystemanalyse' (ZBSA), and from Basel, Switzerland, the Friedrich Miescher Institute for Biomedical Research (FMI). While the core library and algorithms have been initially developed at the LMB, much effort has been put into usability, graphical user interface, preparation of a Windows binary, testing as well as documentation from the Developmental Biology, ZBSA and FMI.
All programming has been done by Mario Emmenlauer (website), Aaron Ponti (website) and Olaf Ronneberger (website).
The xuvtools software and libraries are released under terms of the GPL v2. In case you have questions about this licensing, or want to obtain the software under a different license, please feel free to contact us via email. Commercially licensing is avialable. See bottom of this page for contact information.
Either one of:
Installation and basic usage of the current version of XuvTools is described in the supplied README (or README.shtml) in the doc/ folder of the tools. We also mirror the current version of README.shtml on the web. An example usage with screenshots can be found in the very short quick_manual.pdf.
To keep OpenSource projects like this running, we have to convince our organizations (Insitute, University, Government, ...) to finance these efforts. For this reason we need some statistics, like the number of users, etc. So if you use this software please add your name and optional details into the form below.
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Important notes for the current Release:
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The following test datasets are provided in order to allow direct usage of XuvTools. We have tested stitching on these datasets and provide usage examples as well as run time measurements. If you want to quickly test XuvTools, download one or several of these datasets and give it a try. Note: due to traffic constraints we provide only small datasets in compressed Imaris format. Due to compression, these can take longer to load, which is not a limitation of XuvStitch.
The supplied datasets are copyrighted by the respective owners. You may not distribute them or use them in any publication unless you get a written permission of the respective owner. You need to get a written permission of the respective owner for every usage other than for testing XuvTools on your own personal computer.
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worm5_w1RGB-488nm-s6.ims | C. elegans worm 6 Tiles, 1 channel, 261MB |
by Peter Meister (1) |
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To15100740xm.zip | Neuron filaments 6 Tiles, 1 channel, 132MB |
by Ivan Galimberti (2) |
We appreciate all feedback. For bug reports and feature requests,
please check the ToDo-List first.
To contact us via email check the Authors homepage:
Olaf Ronneberger
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Mario Emmenlauer