.. meta:: :description: Official documentation for vesicle: Volumetric Evaluation of Synaptic Inferfaces using Computer vision at Large Scale :keywords: synapse, connectomics, object detection, computer vision, pipeline .. title:: vesicle .. raw:: html

vesicle: Volumetric Evaluation of Synaptic Inferfaces using Computer vision at Large Scale


vesicle provides a context-aware method for scalable synapse detection in anisotropic electron microscopy data. We provide two methods for object detection: vesicle-rf and vesicle-cnn, which have computational and performance tradeoffs. This work also resulted in the creation of a general-purpose object detection framework that can be used in a LONI pipelining environment. We explain this detection paradigm and provide vesicle-rf code as an example. .. figure:: images/vesicle_banner.jpg :width: 800px :align: center .. raw:: html
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.. sidebar:: vesicle Contact Us If you have questions about vesicle, or have data to analyze, let us know: support@neurodata.io .. toctree:: :maxdepth: 1 :caption: Documentation sphinx/introduction sphinx/local_config sphinx/neurodata sphinx/faq .. toctree:: :maxdepth: 1 :caption: Tutorials tutorials/vesiclerf tutorials/vesiclecnn .. toctree:: :maxdepth: 1 :caption: Paper paper/bmvc paper/results .. toctree:: :maxdepth: 1 :caption: Further Reading api/functions api/loni Gitter chatroom Mailing List Github repo Release Notes If you use vesicle or its data derivatives, please cite: William Gray Roncal, Michael Pekala, Verena Kaynig-Fittkau, Dean M Kleissas, Joshua T Vogelstein, Hanspeter Pfister, Randal Burns, R Jacob Vogelstein, Mark A Chevillet and Gregory D Hager. VESICLE: Volumetric Evaluation of Synaptic Interfaces using Computer Vision at Large Scale. In Xianghua Xie, Mark W. Jones, and Gary K. L. Tam, editors, Proceedings of the British Machine Vision Conference (BMVC), pages 81.1-81.13. BMVA Press, September 2015.