22 citations · 41 across the 5 of their papers we have counts for
5 papers
Guided Proofreading of Automatic Segmentations for Connectomics
Daniel Haehn, Verena Kaynig, James Tompkin +2
Automatic cell image segmentation methods in connectomics produce merge and split errors, which require correction through proofreading. Previous research has identified the visual…
RhoanaNet Pipeline: Dense Automatic Neural Annotation
Seymour Knowles-Barley, Verena Kaynig, Thouis Ray Jones +7
Reconstructing a synaptic wiring diagram, or connectome, from electron microscopy (EM) images of brain tissue currently requires many hours of manual annotation or proofreading (Ka…
Icon: An Interactive Approach to Train Deep Neural Networks for Segmentation of Neuronal Structures
Felix Gonda, Verena Kaynig, Ray Thouis +4
We present an interactive approach to train a deep neural network pixel classifier for the segmentation of neuronal structures. An interactive training scheme reduces the extremely…
Large-Scale Automatic Reconstruction of Neuronal Processes from Electron Microscopy Images
Verena Kaynig, Amelio Vazquez-Reina, Seymour Knowles-Barley +6
Automated sample preparation and electron microscopy enables acquisition of very large image data sets. These technical advances are of special importance to the field of neuroanat…
Visualization in Connectomics
Hanspeter Pfister, Verena Kaynig, Charl P. Botha +4
Connectomics is a field of neuroscience that analyzes neuronal connections. A connectome is a complete map of a neuronal system, comprising all neuronal connections between its str…