2 citations · 3 across the 2 of their papers we have counts for
6 papers · 1 filter
How Shift Equivariance Impacts Metric Learning for Instance Segmentation
Josef Lorenz Rumberger, Xiaoyan Yu, Peter Hirsch +6
Metric learning has received conflicting assessments concerning its suitability for solving instance segmentation tasks. It has been dismissed as theoretically flawed due to the sh…
Microtubule Tracking in Electron Microscopy Volumes
Nils Eckstein, Julia Buhmann, Matthew Cook +1
We present a method for microtubule tracking in electron microscopy volumes. Our method first identifies a sparse set of voxels that likely belong to microtubules. Similar to prior…
Instance Separation Emerges from Inpainting
Steffen Wolf, Fred A. Hamprecht, Jan Funke
Deep neural networks trained to inpaint partially occluded images show a deep understanding of image composition and have even been shown to remove objects from images convincingly…
Synaptic partner prediction from point annotations in insect brains
Julia Buhmann, Renate Krause, Rodrigo Ceballos Lentini +4
High-throughput electron microscopy allows recording of lar- ge stacks of neural tissue with sufficient resolution to extract the wiring diagram of the underlying neural network. C…
Synaptic Cleft Segmentation in Non-Isotropic Volume Electron Microscopy of the Complete Drosophila Brain
Larissa Heinrich, Jan Funke, Constantin Pape +2
Neural circuit reconstruction at single synapse resolution is increasingly recognized as crucially important to decipher the function of biological nervous systems. Volume electron…
The Candidate Multi-Cut for Cell Segmentation
Jan Funke, Chong Zhang, Tobias Pietzsch +1
Two successful approaches for the segmentation of biomedical images are (1) the selection of segment candidates from a merge-tree, and (2) the clustering of small superpixels by so…