@article {47062, title = {Quantitative neuroanatomy for connectomics in Drosophila.}, journal = {eLife}, year = {2016}, month = {2016 Mar 18}, pages = {e12059}, abstract = {

Neuronal circuit mapping using electron microscopy demands laborious proofreading or reconciliation of multiple independent reconstructions. Here, we describe new methods to apply quantitative arbor and network context to iteratively proofread and reconstruct circuits and create anatomically enriched wiring diagrams. We measured the morphological underpinnings of connectivity in new and existing reconstructions of\ Drosophila\ sensorimotor (larva) and visual (adult) systems. Synaptic inputs were preferentially located on numerous small, microtubule-free {\textquoteright}twigs{\textquoteright} which branch off a single microtubule-containing {\textquoteright}backbone{\textquoteright}. Omission of individual twigs accounted for 96\% of errors. However, the synapses of highly connected neurons were distributed across multiple twigs. Thus, the robustness of a strong connection to detailed twig anatomy was associated with robustness to reconstruction error. By comparing iterative reconstruction to the consensus of multiple reconstructions, we show that our method overcomes the need for redundant effort through the discovery and application of relationships between cellular neuroanatomy and synaptic connectivity.

}, doi = {10.7554/eLife.12059}, author = {Schneider-Mizell, Casey M. and Gerhard, Stephan and Longair, Mark and Kazimiers, Tom and Li, Feng and Zwart, Maarten and Champion, Andrew and Midgley, Frank and Fetter, Richard D and Saalfeld, Stephan and Cardona, Albert} } @article {5634, title = {Fiji: an open-source platform for biological-image analysis.}, journal = {Nature Methods}, volume = {9}, year = {2012}, month = {2012 Jul}, pages = {676-82}, abstract = {

Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.

}, keywords = {Algorithms, Animals, Brain, Computational Biology, Computer-Assisted, Drosophila melanogaster, Image Enhancement, Image Processing, Imaging, Information Dissemination, Software, Software Design, Three-Dimensional}, issn = {1548-7105}, doi = {10.1038/nmeth.2019}, author = {Schindelin, Johannes and Arganda-Carreras, Ignacio and Frise, Erwin and Kaynig, Verena and Longair, Mark and Pietzsch, Tobias and Preibisch, Stephan and Rueden, Curtis and Saalfeld, Stephan and Schmid, Benjamin and Tinevez, Jean-Yves and White, Daniel James and Hartenstein, Volker and Eliceiri, Kevin and Tomancak, Pavel and Cardona, Albert} } @article {46785, title = {TrakEM2 software for neural circuit reconstruction.}, journal = {PLoS One}, volume = {7}, year = {2012}, month = {2012}, pages = {e38011}, abstract = {

A key challenge in neuroscience is the expeditious reconstruction of neuronal circuits. For model systems such as Drosophila and C. elegans, the limiting step is no longer the acquisition of imagery but the extraction of the circuit from images. For this purpose, we designed a software application, TrakEM2, that addresses the systematic reconstruction of neuronal circuits from large electron microscopical and optical image volumes. We address the challenges of image volume composition from individual, deformed images; of the reconstruction of neuronal arbors and annotation of synapses with fast manual and semi-automatic methods; and the management of large collections of both images and annotations. The output is a neural circuit of 3d arbors and synapses, encoded in NeuroML and other formats, ready for analysis.

}, keywords = {Animals, Models, Neurological, Nerve Net, Neuroimaging, Neurons, Software, Synapses, Synaptic Transmission}, issn = {1932-6203}, doi = {10.1371/journal.pone.0038011}, author = {Cardona, Albert and Saalfeld, Stephan and Schindelin, Johannes and Arganda-Carreras, Ignacio and Preibisch, Stephan and Longair, Mark and Tomancak, Pavel and Hartenstein, Volker and Douglas, Rodney J} } @article {5684, title = {TrakEM2 software for neural circuit reconstruction.}, journal = {PLoS One}, volume = {7}, year = {2012}, month = {2012}, pages = {e38011}, abstract = {

A key challenge in neuroscience is the expeditious reconstruction of neuronal circuits. For model systems such as Drosophila and C. elegans, the limiting step is no longer the acquisition of imagery but the extraction of the circuit from images. For this purpose, we designed a software application, TrakEM2, that addresses the systematic reconstruction of neuronal circuits from large electron microscopical and optical image volumes. We address the challenges of image volume composition from individual, deformed images; of the reconstruction of neuronal arbors and annotation of synapses with fast manual and semi-automatic methods; and the management of large collections of both images and annotations. The output is a neural circuit of 3d arbors and synapses, encoded in NeuroML and other formats, ready for analysis.

}, keywords = {Animals, Models, Nerve Net, Neuroimaging, Neurological, Neurons, Software, Synapses, Synaptic Transmission}, issn = {1932-6203}, doi = {10.1371/journal.pone.0038011}, author = {Cardona, Albert and Saalfeld, Stephan and Schindelin, Johannes and Arganda-Carreras, Ignacio and Preibisch, Stephan and Longair, Mark and Tomancak, Pavel and Hartenstein, Volker and Douglas, Rodney J} } @article {5691, title = {A high-level 3D visualization API for Java and ImageJ.}, journal = {BMC Bioinformatics}, volume = {11}, year = {2010}, month = {2010}, pages = {274}, abstract = {

Current imaging methods such as Magnetic Resonance Imaging (MRI), Confocal microscopy, Electron Microscopy (EM) or Selective Plane Illumination Microscopy (SPIM) yield three-dimensional (3D) data sets in need of appropriate computational methods for their analysis. The reconstruction, segmentation and registration are best approached from the 3D representation of the data set.

}, keywords = {Automated, Computer Graphics, Computer-Assisted, Confocal, Image Interpretation, Imaging, Microscopy, Pattern Recognition, Programming Languages, Software, Three-Dimensional}, issn = {1471-2105}, doi = {10.1186/1471-2105-11-274}, author = {Schmid, Benjamin and Schindelin, Johannes and Cardona, Albert and Longair, Mark and Heisenberg, Martin.} }