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05/28/15 | BigDataViewer: visualization and processing for large image data sets.
Pietzsch T, Saalfeld S, Preibisch S, Tomancak P
Nature Methods. 2015 May 28;12(6):481-3. doi: 10.1038/nmeth.3392
11/25/14 | Post-acquisition image based compensation for thickness variation in microscopy section series.
Hanslovsky P, Bogovic JA, Saalfeld S
IEEE International Symposium on Biomedical Imaging. 2014 Nov 25:507-11

Serial section Microscopy is an established method for volumetric anatomy reconstruction. Section series imaged with Electron Microscopy are currently vital for the reconstruction of the synaptic connectivity of entire animal brains such as that of Drosophila melanogaster. The process of removing ultrathin layers from a solid block containing the specimen, however, is a fragile procedure and has limited precision with respect to section thickness. We have developed a method to estimate the relative z-position of each individual section as a function of signal change across the section series. First experiments show promising results on both serial section Transmission Electron Microscopy (ssTEM) data and Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) series. We made our solution available as Open Source plugins for the TrakEM2 software and the ImageJ distribution Fiji.

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11/15/12 | ImgLib2--generic image processing in Java.
Pietzsch T, Preibisch S, Tomancak P, Saalfeld S
Bioinformatics. 2012 Nov 15;28(22):3009-11. doi: 10.1093/bioinformatics/bts543

SUMMARY: ImgLib2 is an open-source Java library for n-dimensional data representation and manipulation with focus on image processing. It aims at minimizing code duplication by cleanly separating pixel-algebra, data access and data representation in memory. Algorithms can be implemented for classes of pixel types and generic access patterns by which they become independent of the specific dimensionality, pixel type and data representation. ImgLib2 illustrates that an elegant high-level programming interface can be achieved without sacrificing performance. It provides efficient implementations of common data types, storage layouts and algorithms. It is the data model underlying ImageJ2, the KNIME Image Processing toolbox and an increasing number of Fiji-Plugins.

AVAILABILITY: ImgLib2 is licensed under BSD. Documentation and source code are available at and in a public repository at

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Online.


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07/01/12 | Elastic volume reconstruction from series of ultra-thin microscopy sections.
Saalfeld S, Fetter RD, Cardona A, Tomancak P
Nature Methods. 2012 Jul;9(7):717-20. doi: 10.1038/nmeth.2072

Anatomy of large biological specimens is often reconstructed from serially sectioned volumes imaged by high-resolution microscopy. We developed a method to reassemble a continuous volume from such large section series that explicitly minimizes artificial deformation by applying a global elastic constraint. We demonstrate our method on a series of transmission electron microscopy sections covering the entire 558-cell Caenorhabditis elegans embryo and a segment of the Drosophila melanogaster larval ventral nerve cord.

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06/01/10 | Software for bead-based registration of selective plane illumination microscopy data.
Preibisch S, Saalfeld S, Schindelin J, Tomancak P
Nature Methods. 2010 Jun;7(6):418-9. doi: 10.1038/nmeth0610-418
06/15/10 | As-rigid-as-possible mosaicking and serial section registration of large ssTEM datasets.
Saalfeld S, Cardona A, Hartenstein V, Tomancak P
Bioinformatics. 2010 Jun 15;26(12):i57-63. doi: 10.1093/bioinformatics/btq219

Tiled serial section Transmission Electron Microscopy (ssTEM) is increasingly used to describe high-resolution anatomy of large biological specimens. In particular in neurobiology, TEM is indispensable for analysis of synaptic connectivity in the brain. Registration of ssTEM image mosaics has to recover the 3D continuity and geometrical properties of the specimen in presence of various distortions that are applied to the tissue during sectioning, staining and imaging. These include staining artifacts, mechanical deformation, missing sections and the fact that structures may appear dissimilar in consecutive sections.

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08/01/09 | CATMAID: collaborative annotation toolkit for massive amounts of image data.
Saalfeld S, Cardona A, Hartenstein V, Tomancak P
Bioinformatics. 2009 Aug 1;25(15):1984-6. doi: 10.1093/bioinformatics/btp266

SUMMARY: High-resolution, three-dimensional (3D) imaging of large biological specimens generates massive image datasets that are difficult to navigate, annotate and share effectively. Inspired by online mapping applications like GoogleMaps, we developed a decentralized web interface that allows seamless navigation of arbitrarily large image stacks. Our interface provides means for online, collaborative annotation of the biological image data and seamless sharing of regions of interest by bookmarking. The CATMAID interface enables synchronized navigation through multiple registered datasets even at vastly different scales such as in comparisons between optical and electron microscopy. AVAILABILITY:

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