Ullrich Köthe

发表

Towards a general sampling theory for shape preservation

Peer Stelldinger, Ullrich Köthe, 2005, Image Vis. Comput..

Learning to count with regression forest and structured labels

Ullrich Köthe, Rahul Nair, Luca Fiaschi, 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

Learned Watershed: End-to-End Learning of Seeded Segmentation

Ullrich Köthe, Lukas Schott, Fred A. Hamprecht, 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete Graphical Models

Ullrich Köthe, Jörg H. Kappes, Fred A. Hamprecht, 2012, ECCV.

Low-level Feature Detection Using the Boundary Tensor

Ullrich Köthe, 2006, Visualization and Processing of Tensor Fields.

Edge and Junction Detection with an Improved Structure Tensor

Ullrich Köthe, U. Köthe, 2003, DAGM-Symposium.

Computational protein profile similarity screening for quantitative mass spectrometry experiments

Ullrich Köthe, Bernhard Y. Renard, Hanno Steen, 2010, Bioinform..

On Oblique Random Forests

Ullrich Köthe, Bjoern H. Menze, Fred A. Hamprecht, 2011, ECML/PKDD.

Using an n-zone TDI camera for acquisition of multiple images with different illuminations in a single scan

Ullrich Köthe, Ralf Zink, Colin Flood, 2013 .

GET: The Connection Between Monogenic Scale-Space and Gaussian Derivatives

Michael Felsberg, Ullrich Köthe, M. Felsberg, 2005, Scale-Space.

Conditional Invertible Neural Networks for Guided Image Generation

Ullrich Köthe, Lynton Ardizzone, Carsten Rother, 2019 .

XPMaps and Topological Segmentation - A Unified Approach to Finite Topologies in the Plane

Ullrich Köthe, U. Köthe, 2002, DGCI.

Carving: Scalable Interactive Segmentation of Neural Volume Electron Microscopy Images

Ullrich Köthe, Fred A. Hamprecht, Christoph N. Straehle, 2011, MICCAI.

The GeoMap: A Unified Representation for Topology and Geometry

Ullrich Köthe, Hans Meine, U. Köthe, 2005, GbRPR.

What Can We Learn from Discrete Images about the Continuous World?

Ullrich Köthe, 2008, DGCI.

Probabilistic image segmentation with closedness constraints

Ullrich Köthe, Jörg H. Kappes, Fred A. Hamprecht, 2011, 2011 International Conference on Computer Vision.

Shape Preserving Digitization of Binary Images After Blurring

Peer Stelldinger, Ullrich Köthe, 2005, DGCI.

Provably Correct Edgel Linking and Subpixel Boundary Reconstruction

Peer Stelldinger, Ullrich Köthe, Hans Meine, 2006, DAGM-Symposium.

Local Appropriate Scale in Morphological Scale-Space

Ullrich Köthe, U. Köthe, 1996, ECCV.

SIMA: Simultaneous Multiple Alignment of LC/MS Peak Lists

Ullrich Köthe, Bernhard Y. Renard, Fred A. Hamprecht, 2011, Bioinform..

Pixel Approximation Errors in Common Watershed Algorithms

Peer Stelldinger, Ullrich Köthe, Hans Meine, 2009, DGCI.

BayesFlow: Learning Complex Stochastic Models With Invertible Neural Networks

Ullrich Köthe, Stefan T. Radev, Lynton Ardizzone, 2020, IEEE Transactions on Neural Networks and Learning Systems.

A New Sub-pixel Map for Image Analysis

Ullrich Köthe, Hans Meine, 2006, IWCIA.

Generic Programming Techniques that Make Planar Cell Complexes Easy to Use

Ullrich Köthe, 2000, Digital and Image Geometry.

Ilastik: Interactive learning and segmentation toolkit

Ullrich Köthe, Fred A. Hamprecht, Christoph Sommer, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Towards end-to-end likelihood-free inference with convolutional neural networks.

Ullrich Köthe, Stefan T. Radev, Andreas Voss, 2020, The British journal of mathematical and statistical psychology.

Deriving Topological Representations from Edge Images

Ullrich Köthe, U. Köthe, 2002, Theoretical Foundations of Computer Vision.

Accurate and Efficient Approximation of the Continuous Gaussian Scale-Space

Ullrich Köthe, 2004, DAGM-Symposium.

Integrated Edge and Junction Detection with the Boundary Tensor

Ullrich Köthe, U. Köthe, 2003, ICCV.

Learning to segment dense cell nuclei with shape prior

Ullrich Köthe, Fred A. Hamprecht, Xinghua Lou, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

Asymmetric Cuts: Joint Image Labeling and Partitioning

Ullrich Köthe, Thorben Kröger, Jörg H. Kappes, 2014, GCPR.

Exact Information Bottleneck with Invertible Neural Networks: Getting the Best of Discriminative and Generative Modeling pdf

Ullrich Köthe, Radek Mackowiak, Lynton Ardizzone, 2020, ArXiv.

Geometric Analysis of 3D Electron Microscopy Data

Ullrich Köthe, Thorben Kröger, Fred A. Hamprecht, 2010, WADGMM.

3D segmentation of SBFSEM images of neuropil by a graphical model over supervoxel boundaries

Ullrich Köthe, Thorben Kröger, Moritz Helmstaedter, 2012, Medical Image Anal..

Weakly Supervised Learning of Image Partitioning Using Decision Trees with Structured Split Criteria

Ullrich Köthe, Fred A. Hamprecht, Christoph N. Straehle, 2013, 2013 IEEE International Conference on Computer Vision.

Quality Classification of Microscopic Imagery with Weakly Supervised Learning

Ullrich Köthe, Luca Fiaschi, Fred A. Hamprecht, 2012, MLMI.

Graphical model for joint segmentation and tracking of multiple dividing cells

Ullrich Köthe, Fred A. Hamprecht, Carsten Haubold, 2015, Bioinform..

HINT: Hierarchical Invertible Neural Transport for General and Sequential Bayesian inference pdf

Ullrich Köthe, Carsten Rother, Robert Scheichl, 2019, ArXiv.

On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation

Ullrich Köthe, Fred A. Hamprecht, Daniel Kondermann, 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks

Ullrich Köthe, Lena Maier-Hein, Tim J. Adler, 2019, International Journal of Computer Assisted Radiology and Surgery.

Guided Image Generation with Conditional Invertible Neural Networks pdf

Ullrich Köthe, Carsten Rother, Lynton Ardizzone, 2019, ArXiv.

Riesz-Transforms Versus Derivatives: On the Relationship Between the Boundary Tensor and the Energy Tensor

Michael Felsberg, Ullrich Köthe, M. Felsberg, 2005, Scale-Space.

K-Smallest Spanning Tree Segmentations

Ullrich Köthe, Fred A. Hamprecht, Christoph N. Straehle, 2013, GCPR.

Cut, Glue, & Cut: A Fast, Approximate Solver for Multicut Partitioning

Ullrich Köthe, Thorben Kröger, Jörg H. Kappes, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

Multiple Instance Learning with Response-Optimized Random Forests

Ullrich Köthe, Melih Kandemir, Fred A. Hamprecht, 2014, 2014 22nd International Conference on Pattern Recognition.

Tracking Indistinguishable Translucent Objects over Time Using Weakly Supervised Structured Learning

Ullrich Köthe, Luca Fiaschi, Fred A. Hamprecht, 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

The Mutex Watershed and its Objective: Efficient, Parameter-Free Image Partitioning

Ullrich Köthe, Fred A. Hamprecht, Steffen Wolf, 2019, ArXiv.

Benchmarking Invertible Architectures on Inverse Problems

Ullrich Köthe, Lynton Ardizzone, Carsten Rother, 2021, ArXiv.

A topological sampling theorem for Robust boundary reconstruction and image segmentation

Peer Stelldinger, Ullrich Köthe, Hans Meine, 2009, Discret. Appl. Math..

A Discrete Chain Graph Model for 3d+t Cell Tracking with High Misdetection Robustness

Ullrich Köthe, Fred A. Hamprecht, Lars Hufnagel, 2012, ECCV.

Runtime-Flexible Multi-dimensional Arrays and Views for C++98 and C++0x pdf

Ullrich Köthe, Thorben Kröger, Fred A. Hamprecht, 2010, ArXiv.

Shape Preservation during Digitization: Tight Bounds Based on the Morphing Distance

Peer Stelldinger, Ullrich Köthe, 2003, DAGM-Symposium.

Boundary Characterization Within the Wedge-Channel Representation

Ullrich Köthe, 2004, IWCM.

Fast and Accurate Interactive Image Segmentation in the GEOMAP Framework

Ullrich Köthe, H. Siegfried Stiehl, Hans Meine, 2004, Bildverarbeitung für die Medizin.

Learning Robust Models Using The Principle of Independent Causal Mechanisms pdf

Ullrich Köthe, Lynton Ardizzone, Carsten Rother, 2020, ArXiv.

HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference

Ullrich Köthe, Robert Scheichl, Gianluca Detommaso, 2019 .

The Mutex Watershed: Efficient, Parameter-Free Image Partitioning

Ullrich Köthe, Fred A. Hamprecht, Steffen Wolf, 2018, ECCV.

The Lazy Flipper: MAP Inference in Higher-Order Graphical Models by Depth-limited Exhaustive Search pdf

Ullrich Köthe, Jörg H. Kappes, Fred A. Hamprecht, 2010, ArXiv.

An Efficient Fusion Move Algorithm for the Minimum Cost Lifted Multicut Problem

Ullrich Köthe, Fred A. Hamprecht, Björn Andres, 2016, ECCV.

Fast and Accurate 3D Edge Detection for Surface Reconstruction

Peer Stelldinger, Ullrich Köthe, Christian Bähnisch, 2009, DAGM-Symposium.

Primary Image Segmentation

Ullrich Köthe, U. Köthe, 1995, DAGM-Symposium.

Topologically Correct Image Segmentation Using Alpha Shapes

Peer Stelldinger, Ullrich Köthe, Hans Meine, 2006, DGCI.

The STL Model in the Geometric Domain

Ullrich Köthe, Karsten Weihe, 1998, Generic Programming.

Amortized Bayesian Model Comparison With Evidential Deep Learning pdf

Ullrich Köthe, Stefan T. Radev, Paul-Christian Bürkner, 2020, IEEE Transactions on Neural Networks and Learning Systems.

Learning to Segment Neurons with Non-local Quality Measures

Ullrich Köthe, Thorben Kröger, Fred A. Hamprecht, 2013, MICCAI.

Proof-reading guidance in cell tracking by sampling from tracking-by-assignment models

Ullrich Köthe, Fred A. Hamprecht, Steffen Wolf, 2015, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI).

Design Patterns for Independent Building Blocks

Ullrich Köthe, 1998, EuroPLoP.

Multivariate Watershed Segmentation of Compositional Data

Ullrich Köthe, Bernhard Y. Renard, Fred A. Hamprecht, 2009, DGCI.

Globally Optimal Closed-Surface Segmentation for Connectomics

Ullrich Köthe, Thorben Kröger, Fred A. Hamprecht, 2012, ECCV.

How to Extract the Geometry and Topology from Very Large 3D Segmentations pdf

Ullrich Köthe, Thorben Kröger, Fred A. Hamprecht, 2010, ArXiv.

Automatic cardiac MRI myocardium segmentation using graphcut

Max A. Viergever, Ullrich Köthe, Wiro J. Niessen, 2006, SPIE Medical Imaging.

Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN) pdf

Ullrich Köthe, Carsten Rother, Peter Sorrenson, 2020, ICLR.

Object Segmentation using Pixel-wise Adversarial Loss pdf

Ullrich Köthe, Janis Keuper, Franz-Josef Pfreundt, 2019, GCPR.

Shape Preserving Digitization of Ideal and Blurred Binary Images

Peer Stelldinger, Ullrich Köthe, 2003, DGCI.

Deltr: Digital embryo lineage tree reconstructor

Ullrich Köthe, Fred A. Hamprecht, Burkhard Hockendorf, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Connectivity preserving digitization of blurred binary images in 2D and 3D

Peer Stelldinger, Ullrich Köthe, 2006, Comput. Graph..

Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification

Ullrich Köthe, Moritz Helmstaedter, Fred A. Hamprecht, 2008, DAGM-Symposium.

Automated segmentation of synapses in 3D EM data

Ullrich Köthe, Fred A. Hamprecht, Anna Kreshuk, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Quantitative Assessment of Image Segmentation Quality by Random Walk Relaxation Times

Ullrich Köthe, Fred A. Hamprecht, Boaz Nadler, 2009, DAGM-Symposium.

Improving 3D EM data segmentation by joint optimization over boundary evidence and biological priors

Ullrich Köthe, Fred A. Hamprecht, Thorsten Beier, 2015, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI).

Invertible Neural Networks for Uncertainty Quantification in Photoacoustic Imaging pdf

Ullrich Köthe, Janek Gröhl, Lena Maier-Hein, 2020, Bildverarbeitung für die Medizin.

Training Invertible Neural Networks as Autoencoders

Ullrich Köthe, Lynton Ardizzone, The-Gia Leo Nguyen, 2019, GCPR.

Deuteration distribution estimation with improved sequence coverage for HX/MS experiments

Ullrich Köthe, Bernhard Y. Renard, Hanno Steen, 2010, Bioinform..

An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM

Ullrich Köthe, Christoph Schnörr, Jörg H. Kappes, 2010, DAGM-Symposium.

Analyzing Inverse Problems with Invertible Neural Networks pdf

Ullrich Köthe, Lena Maier-Hein, Lynton Ardizzone, 2018, ICLR.

Seeded watershed cut uncertainty estimators for guided interactive segmentation

Ullrich Köthe, Fred A. Hamprecht, Winfried Denk, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

ViComp - Architektur und Städteplanung mit virtueller Modellierung und Komposition

Ullrich Köthe, Andreas Schlempp, 1997, SimVis.

SimpleSTORM: a fast, self-calibrating reconstruction algorithm for localization microscopy

Ullrich Köthe, Fred A. Hamprecht, Ilia Kats, 2014, Histochemistry and Cell Biology.

HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference

Ullrich Köthe, Robert Scheichl, Gianluca Detommaso, 2019, AAAI.

Invertible neural networks for uncertainty quantification in photoacoustic imaging

Ullrich Köthe, Lena Maier-Hein, Janek Gröhl, 2021 .

OutbreakFlow: Model-based Bayesian inference of disease outbreak dynamics with invertible neural networks and its application to the COVID-19 pandemics in Germany

Ullrich Köthe, Stefan T. Radev, Till Bärnighausen, 2020, PLoS Comput. Biol..

Requested Interface

Ullrich Köthe, 1997 .

Gradient-Based Segmentation Requires Doubling of the Sampling Rate

Ullrich Köthe, 2003 .

SEGMENTATION WITH THE EXACT WATERSHED TRANSFORM

Ullrich Köthe, Hans Meine, 2005 .