1 code implementation • ICCV 2023 • Steffen Wolf, Manan Lalit, Henry Westmacott, Katie McDole, Jan Funke
Here, we show theoretically that, under assumptions commonly found in microscopy images, OCEs can be learnt through a self-supervised task that predicts the spatial offset between image patches.
1 code implementation • 24 Aug 2022 • Peter Hirsch, Caroline Malin-Mayor, Anthony Santella, Stephan Preibisch, Dagmar Kainmueller, Jan Funke
Our work specifically addresses the following challenging properties of C. elegans embryo recordings: (1) Many cell divisions as compared to benchmark recordings of other organisms, and (2) the presence of polar bodies that are easily mistaken as cell nuclei.
no code implementations • 28 Sep 2021 • Nils Eckstein, Alexander S. Bates, Gregory S. X. E. Jefferis, Jan Funke
We present a method for neural network interpretability by combining feature attribution with counterfactual explanations to generate attribution maps that highlight the most discriminative features between pairs of classes.
1 code implementation • ICCV 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.
1 code implementation • 17 Sep 2020 • Nils Eckstein, Julia Buhmann, Matthew Cook, Jan Funke
We present a method for microtubule tracking in electron microscopy volumes.
no code implementations • 28 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.
no code implementations • 21 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.
no code implementations • 7 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.
1 code implementation • IEEE Transactions on Pattern Analysis and Machine Intelligence 2018 • Jan Funke, Fabian David Tschopp, William Grisaitis, Arlo Sheridan, Chandan Singh, Stephan Saalfeld, Srinivas C. Turaga
Our extension consists of two parts: First, we present a quasi-linear method to compute the loss gradient, improving over the original quadratic algorithm.
Ranked #1 on Brain Image Segmentation on FIB-25 Synaptic Sites
no code implementations • 4 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.
1 code implementation • 8 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.