Search Results for author: Jan Funke

Found 8 papers, 4 papers with code

How Shift Equivariance Impacts Metric Learning for Instance Segmentation

1 code implementation14 Jan 2021 Josef Lorenz Rumberger, Xiaoyan Yu, Peter Hirsch, Melanie Dohmen, Vanessa Emanuela Guarino, Ashkan Mokarian, Lisa Mais, Jan Funke, Dagmar Kainmueller

In our work, we contribute a comprehensive formal analysis of the shift equivariance properties of encoder-decoder-style CNNs, which yields a clear picture of what can and cannot be achieved with metric learning in the face of same-looking objects.

Instance Segmentation Metric Learning +1

Microtubule Tracking in Electron Microscopy Volumes

1 code implementation17 Sep 2020 Nils Eckstein, Julia Buhmann, Matthew Cook, Jan Funke

We present a method for microtubule tracking in electron microscopy volumes.

Electron Microscopy

Instance Separation Emerges from Inpainting

no code implementations28 Feb 2020 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

no code implementations21 Jun 2018 Julia Buhmann, Renate Krause, Rodrigo Ceballos Lentini, Nils Eckstein, Matthew Cook, Srinivas Turaga, Jan Funke

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.

Electron Microscopy

Synaptic Cleft Segmentation in Non-Isotropic Volume Electron Microscopy of the Complete Drosophila Brain

no code implementations7 May 2018 Larissa Heinrich, Jan Funke, Constantin Pape, Juan Nunez-Iglesias, Stephan Saalfeld

Neural circuit reconstruction at single synapse resolution is increasingly recognized as crucially important to decipher the function of biological nervous systems.

Electron Microscopy

The Candidate Multi-Cut for Cell Segmentation

no code implementations4 Jul 2017 Jan Funke, Chong Zhang, Tobias Pietzsch, Stephan Saalfeld

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 solving a Multi-Cut problem.

Cell Segmentation Electron Microscopy

TED: A Tolerant Edit Distance for Segmentation Evaluation

1 code implementation8 Mar 2015 Jan Funke, Francesc Moreno-Noguer, Albert Cardona, Matthew Cook

This measure, which we call Tolerant Edit Distance (TED), is motivated by two observations: (1) Some errors, like small boundary shifts, are tolerable in practice.

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