Hannes Nickisch

According to our database, Hannes Nickisch authored at least 48 papers between 2008 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Delineation of coronary stents in intravascular ultrasound pullbacks.

Tobias Wissel, Katharina A. Riedl, Klaus Schaefers, Hannes Nickisch, Fabian J. Brunner, Nikolas Schnellbächer, Stefan Blankenberg, Moritz Seiffert, Michael Grass

Proceedings of the Medical Imaging 2021: Image-Guided Procedures, 2021

Machine-learning-based clinical plaque detection using a synthetic plaque lesion model for coronary CTA.

Nikolas Schnellbächer, Haissam Ragab, Hannes Nickisch, Tobias Wissel, Clemens Spink, Gunnar Lund, Michael Grass

Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021

Multi-Resolution 3D Convolutional Neural Networks for Automatic Coronary Centerline Extraction in Cardiac CT Angiography Scans.

Zohaib Salahuddin, Matthias Lenga, Hannes Nickisch

Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

2020

Learning metal artifact reduction in cardiac CT images with moving pacemakers.

Tanja Lossau, Hannes Nickisch, Tobias Wissel, Michael M. Morlock, Michael Grass

Medical Image Anal., 2020

Intelligent Chest X-ray Worklist Prioritization by CNNs: A Clinical Workflow Simulation.

Ivo M. Baltruschat, Leonhard Steinmeister, Hannes Nickisch, Axel Saalbach, Michael Grass, Gerhard Adam, Harald Ittrich, Tobias Knopp

CoRR, 2020

2019

Motion artifact recognition and quantification in coronary CT angiography using convolutional neural networks.

Tanja Lossau, Hannes Nickisch, Tobias Wissel, Rolf Bippus, Holger Schmitt, Michael M. Morlock, Michael Grass

Medical Image Anal., 2019

Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction.

William Herlands, Daniel B. Neill, Hannes Nickisch, Andrew Gordon Wilson

J. Mach. Learn. Res., 2019

Improving CCTA based lesions' hemodynamic significance assessment by accounting for partial volume modeling in automatic coronary lumen segmentation.

Moti Freiman, Hannes Nickisch, Sven Prevrhal, Holger Schmitt, Mani Vembar, Pál Maurovich-Horvat, Patrick Donnelly, Liran Goshen

CoRR, 2019

Motion estimation and correction in cardiac CT angiography images using convolutional neural networks.

Tanja Lossau, Hannes Nickisch, Tobias Wissel, Rolf-Dieter Bippus, Holger Schmitt, Michael M. Morlock, Michael Grass

Comput. Medical Imaging Graph., 2019

Dynamic Pacemaker Artifact Removal (DyPAR) from CT Data using CNNs.

Tanja Lossau, Hannes Nickisch, Tobias Wissel, Samer Hakmi, Clemens Spink, Michael M. Morlock, Michael Grass

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2019

How to Learn from Unlabeled Volume Data: Self-supervised 3D Context Feature Learning.

Maximilian Blendowski, Hannes Nickisch, Mattias P. Heinrich

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

When Does Bone Suppression And Lung Field Segmentation Improve Chest X-Ray Disease Classification?

Ivo M. Baltruschat, Leonhard Steinmeister, Harald Ittrich, Gerhard Adam, Hannes Nickisch, Axel Saalbach, Jens von Berg, Michael Grass, Tobias Knopp

Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Abstract: Does Bone Suppression and Lung Detection Improve Chest Disease Classification?

Ivo M. Baltruschat, Leonhard Steinmeister, Harald Ittrich, Gerhard Adam, Hannes Nickisch, Axel Saalbach, Jens von Berg, Michael Grass, Tobias Knopp

Proceedings of the Bildverarbeitung für die Medizin 2019 - Algorithmen - Systeme, 2019

2018

Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification.

Ivo M. Baltruschat, Hannes Nickisch, Michael Grass, Tobias Knopp, Axel Saalbach

CoRR, 2018

Nearest neighbor 3D segmentation with context features.

Evelin Hristova, Heinrich Schulz, Tom Brosch, Mattias P. Heinrich, Hannes Nickisch

Proceedings of the Medical Imaging 2018: Image Processing, 2018

Deep-learning-based CT motion artifact recognition in coronary arteries.

Tanja Elss, Hannes Nickisch, Tobias Wissel, Holger Schmitt, Mani Vembar, Michael M. Morlock, Michael Grass

Proceedings of the Medical Imaging 2018: Image Processing, 2018

Orientation regression in hand radiographs: a transfer learning approach.

Ivo M. Baltruschat, Axel Saalbach, Mattias P. Heinrich, Hannes Nickisch, Sascha Jockel

Proceedings of the Medical Imaging 2018: Image Processing, 2018

State Space Gaussian Processes with Non-Gaussian Likelihood.

Hannes Nickisch, Arno Solin, Alexander Grigorevskiy

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Scalable Log Determinants for Gaussian Process Kernel Learning.

Kun Dong, David Eriksson, Hannes Nickisch, David Bindel, Andrew Gordon Wilson

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Learning a Sparse Database for Patch-Based Medical Image Segmentation.

Moti Freiman, Hannes Nickisch, Holger Schmitt, Pál Maurovich-Horvat, Patrick Donnelly, Mani Vembar, Liran Goshen

Proceedings of the Patch-Based Techniques in Medical Imaging, 2017

2016

Automatic coronary lumen segmentation with partial volume modeling improves lesions' hemodynamic significance assessment.

Moti Freiman, Yechiel Lamash, Guy Gilboa, Hannes Nickisch, Sven Prevrhal, Holger Schmitt, Mani Vembar, Liran Goshen

Proceedings of the Medical Imaging 2016: Image Processing, 2016

SVM-based failure detection of GHT localizations.

Thomas Blaffert, Cristian Lorenz, Hannes Nickisch, Jochen Peters, Jürgen Weese

Proceedings of the Medical Imaging 2016: Image Processing, 2016

Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces.

William Herlands, Andrew Gordon Wilson, Hannes Nickisch, Seth R. Flaxman, Daniel B. Neill, Wilbert Van Panhuis, Eric P. Xing

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015

Thoughts on Massively Scalable Gaussian Processes.

Andrew Gordon Wilson, Christoph Dann, Hannes Nickisch

CoRR, 2015

Can Pretrained Neural Networks Detect Anatomy?

Vlado Menkovski, Zharko Aleksovski, Axel Saalbach, Hannes Nickisch

CoRR, 2015

Learning Patient-Specific Lumped Models for Interactive Coronary Blood Flow Simulations.

Hannes Nickisch, Yechiel Lamash, Sven Prevrhal, Moti Freiman, Mani Vembar, Liran Goshen, Holger Schmitt

Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 2015

Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP).

Andrew Gordon Wilson, Hannes Nickisch

Proceedings of the 32nd International Conference on Machine Learning, 2015

Fast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods.

Seth R. Flaxman, Andrew Gordon Wilson, Daniel B. Neill, Hannes Nickisch, Alexander J. Smola

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Attribute-Based Classification for Zero-Shot Visual Object Categorization.

Christoph H. Lampert, Hannes Nickisch, Stefan Harmeling

IEEE Trans. Pattern Anal. Mach. Intell., 2014

2013

Generating anatomical models of the heart and the aorta from medical images for personalized physiological simulations.

Jürgen Weese, Alexandra Groth, Hannes Nickisch, Hans Barschdorf, Frank M. Weber, Jérôme Velut, Miguel Castro, Christine Toumoulin, Jean-Louis Coatrieux, Mathieu De Craene, Gemma Piella, Catalina Tobon-Gomez, Alejandro F. Frangi, David C. Barber, Izra Valverde, Yubing Shi, Cristina Staicu, A. Brown, Philipp Beerbaum, D. Rodney Hose

Medical Biol. Eng. Comput., 2013

2012

Generating feature spaces for linear algorithms with regularized sparse kernel slow feature analysis.

Wendelin Böhmer, Steffen Grünewälder, Hannes Nickisch, Klaus Obermayer

Mach. Learn., 2012

glm-ie: Generalised Linear Models Inference & Estimation Toolbox.

Hannes Nickisch

J. Mach. Learn. Res., 2012

User-Centric Learning and Evaluation of Interactive Segmentation Systems.

Pushmeet Kohli, Hannes Nickisch, Carsten Rother, Christoph Rhemann

Int. J. Comput. Vis., 2012

From Image to Personalized Cardiac Simulation: Encoding Anatomical Structures into a Model-Based Segmentation Framework.

Hannes Nickisch, Hans Barschdorf, Frank M. Weber, Martin W. Krueger, Olaf Dössel, Jürgen Weese

Proceedings of the Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges, 2012

2011

Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models.

Matthias W. Seeger, Hannes Nickisch

SIAM J. Imaging Sci., 2011

Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference.

Matthias W. Seeger, Hannes Nickisch

Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Regularized Sparse Kernel Slow Feature Analysis.

Wendelin Böhmer, Steffen Grünewälder, Hannes Nickisch, Klaus Obermayer

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Additive Gaussian Processes.

David Duvenaud, Hannes Nickisch, Carl Edward Rasmussen

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010

Bayesian inference and experimental design for large generalised linear models.

Hannes Nickisch

PhD thesis, 2010

Gaussian Processes for Machine Learning (GPML) Toolbox.

Carl Edward Rasmussen, Hannes Nickisch

J. Mach. Learn. Res., 2010

Learning an interactive segmentation system.

Hannes Nickisch, Carsten Rother, Pushmeet Kohli, Christoph Rhemann

Proceedings of the Seventh Indian Conference on Computer Vision, 2010

Gaussian Mixture Modeling with Gaussian Process Latent Variable Models.

Hannes Nickisch, Carl Edward Rasmussen

Proceedings of the Pattern Recognition, 2010

2009

Learning an Interactive Segmentation System

Hannes Nickisch, Pushmeet Kohli, Carsten Rother

CoRR, 2009

Convex variational Bayesian inference for large scale generalized linear models.

Hannes Nickisch, Matthias W. Seeger

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

Large Scale Variational Inference and Experimental Design for Sparse Generalized Linear Models.

Matthias W. Seeger, Hannes Nickisch

Proceedings of the Sampling-based Optimization in the Presence of Uncertainty, 26.04., 2009

Learning to detect unseen object classes by between-class attribute transfer.

Christoph H. Lampert, Hannes Nickisch, Stefan Harmeling

Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2009), 2009

2008

Bayesian Experimental Design of Magnetic Resonance Imaging Sequences.

Matthias W. Seeger, Hannes Nickisch, Rolf Pohmann, Bernhard Schölkopf

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Compressed sensing and Bayesian experimental design.

Matthias W. Seeger, Hannes Nickisch

Proceedings of the Machine Learning, 2008