Hannes Nickisch

ORCID

Publication Activity (10 Years)

Years Active: 2008-2021
Publications (10 Years): 28

Top Venues

CoRR

Medical Imaging: Image Processing

ICML

ISBI

Berlin Institute of Technology (PHD)

Education History

Berlin Institute of Technology

PHD

Publications

Zohaib Salahuddin, Matthias Lenga, Hannes Nickisch
Multi-Resolution 3D Convolutional Neural Networks for Automatic Coronary Centerline Extraction in Cardiac CT Angiography Scans. ISBI (2021)
Tobias Wissel, Katharina A. Riedl, Klaus Schaefers, Hannes Nickisch, Fabian J. Brunner, Nikolas Schnellbächer, Stefan Blankenberg, Moritz Seiffert, Michael Grass
Delineation of coronary stents in intravascular ultrasound pullbacks. Medical Imaging: Image-Guided Procedures (2021)
Nikolas Schnellbächer, Haissam Ragab, Hannes Nickisch, Tobias Wissel, Clemens Spink, Gunnar Lund, Michael Grass
Machine-learning-based clinical plaque detection using a synthetic plaque lesion model for coronary CTA. Medical Imaging: Computer-Aided Diagnosis (2021)
Zohaib Salahuddin, Matthias Lenga, Hannes Nickisch
Multi-Resolution 3D Convolutional Neural Networks for Automatic Coronary Centerline Extraction in Cardiac CT Angiography Scans. CoRR (2020)
Ivo M. Baltruschat, Leonhard Steinmeister, Hannes Nickisch, Axel Saalbach, Michael Grass, Gerhard Adam, Harald Ittrich, Tobias Knopp
Intelligent Chest X-ray Worklist Prioritization by CNNs: A Clinical Workflow Simulation. CoRR (2020)
Tanja Lossau, Hannes Nickisch, Tobias Wissel, Michael M. Morlock, Michael Grass
Learning metal artifact reduction in cardiac CT images with moving pacemakers. Medical Image Anal. 61 (2020)
Ivo M. Baltruschat, Leonhard Steinmeister, Harald Ittrich, Gerhard Adam, Hannes Nickisch, Axel Saalbach, Jens von Berg, Michael Grass, Tobias Knopp
When Does Bone Suppression And Lung Field Segmentation Improve Chest X-Ray Disease Classification? ISBI (2019)
Maximilian Blendowski, Hannes Nickisch, Mattias P. Heinrich
How to Learn from Unlabeled Volume Data: Self-supervised 3D Context Feature Learning. MICCAI (6) (2019)
William Herlands, Daniel B. Neill, Hannes Nickisch, Andrew Gordon Wilson
Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction. J. Mach. Learn. Res. 20 (2019)
Moti Freiman, Hannes Nickisch, Holger Schmitt, Pal Maurovich-Horvat, Patrick Donnelly, Mani Vembar, Liran Goshen
Learning a sparse database for patch-based medical image segmentation. CoRR (2019)
Tanja Lossau, Hannes Nickisch, Tobias Wissel, Rolf-Dieter Bippus, Holger Schmitt, Michael M. Morlock, Michael Grass
Motion estimation and correction in cardiac CT angiography images using convolutional neural networks. Comput. Medical Imaging Graph. 76 (2019)
Ivo M. Baltruschat, Leonhard Steinmeister, Harald Ittrich, Gerhard Adam, Hannes Nickisch, Axel Saalbach, Jens von Berg, Michael Grass, Tobias Knopp
Abstract: Does Bone Suppression and Lung Detection Improve Chest Disease Classification? Bildverarbeitung für die Medizin (2019)
Tanja Lossau, Hannes Nickisch, Tobias Wissel, Samer Hakmi, Clemens Spink, Michael M. Morlock, Michael Grass
Dynamic Pacemaker Artifact Removal (DyPAR) from CT Data using CNNs. MIDL (2019)
Tanja Lossau, Hannes Nickisch, Tobias Wissel, Rolf Bippus, Holger Schmitt, Michael M. Morlock, Michael Grass
Motion artifact recognition and quantification in coronary CT angiography using convolutional neural networks. Medical Image Anal. 52 (2019)
Moti Freiman, Hannes Nickisch, Sven Prevrhal, Holger Schmitt, Mani Vembar, Pal Maurovich-Horvat, Patrick Donnelly, Liran Goshen
Improving CCTA based lesions' hemodynamic significance assessment by accounting for partial volume modeling in automatic coronary lumen segmentation. CoRR (2019)
Ivo M. Baltruschat, Hannes Nickisch, Michael Grass, Tobias Knopp, Axel Saalbach
Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification. CoRR (2018)
Ivo M. Baltruschat, Axel Saalbach, Mattias P. Heinrich, Hannes Nickisch, Sascha Jockel
Orientation regression in hand radiographs: a transfer learning approach. Medical Imaging: Image Processing (2018)
Hannes Nickisch, Arno Solin, Alexander Grigorevskiy
State Space Gaussian Processes with Non-Gaussian Likelihood. ICML (2018)
Ivo M. Baltruschat, Leonhard Steinmeister, Harald Ittrich, Gerhard Adam, Hannes Nickisch, Axel Saalbach, Jens von Berg, Michael Grass, Tobias Knopp
When does Bone Suppression and Lung Field Segmentation Improve Chest X-Ray Disease Classification? CoRR (2018)
William Herlands, Daniel B. Neill, Hannes Nickisch, Andrew Gordon Wilson
Change Surfaces for Expressive Multidimensional Changepoints and Counterfactual Prediction. CoRR (2018)
Tanja Elss, Hannes Nickisch, Tobias Wissel, Holger Schmitt, Mani Vembar, Michael M. Morlock, Michael Grass
Deep-learning-based CT motion artifact recognition in coronary arteries. Medical Imaging: Image Processing (2018)
Evelin Hristova, Heinrich Schulz, Tom Brosch, Mattias P. Heinrich, Hannes Nickisch
Nearest neighbor 3D segmentation with context features. Medical Imaging: Image Processing (2018)
Moti Freiman, Hannes Nickisch, Holger Schmitt, Pal Maurovich-Horvat, Patrick Donnelly, Mani Vembar, Liran Goshen
Learning a Sparse Database for Patch-Based Medical Image Segmentation. Patch-MI@MICCAI (2017)
Kun Dong, David Eriksson, Hannes Nickisch, David Bindel, Andrew Gordon Wilson
Scalable Log Determinants for Gaussian Process Kernel Learning. NIPS (2017)
Kun Dong, David Eriksson, Hannes Nickisch, David Bindel, Andrew Gordon Wilson
Scalable Log Determinants for Gaussian Process Kernel Learning. CoRR (2017)
William Herlands, Andrew Gordon Wilson, Hannes Nickisch, Seth R. Flaxman, Daniel B. Neill, Wilbert Van Panhuis, Eric P. Xing
Scalable Gaussian Processes for Characterizing Multidimensional Change Surfaces. AISTATS (2016)
Thomas Blaffert, Cristian Lorenz, Hannes Nickisch, Jochen Peters, Jürgen Weese
SVM-based failure detection of GHT localizations. Medical Imaging: Image Processing (2016)
Moti Freiman, Yechiel Lamash, Guy Gilboa, Hannes Nickisch, Sven Prevrhal, Holger Schmitt, Mani Vembar, Liran Goshen
Automatic coronary lumen segmentation with partial volume modeling improves lesions' hemodynamic significance assessment. Medical Imaging: Image Processing (2016)
Andrew Gordon Wilson, Hannes Nickisch
Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP). ICML (2015)
Seth R. Flaxman, Andrew Gordon Wilson, Daniel B. Neill, Hannes Nickisch, Alexander J. Smola
Fast Kronecker Inference in Gaussian Processes with non-Gaussian Likelihoods. ICML (2015)
Andrew Gordon Wilson, Hannes Nickisch
Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP). CoRR (2015)
Hannes Nickisch, Yechiel Lamash, Sven Prevrhal, Moti Freiman, Mani Vembar, Liran Goshen, Holger Schmitt
Learning Patient-Specific Lumped Models for Interactive Coronary Blood Flow Simulations. MICCAI (2) (2015)
Vlado Menkovski, Zharko Aleksovski, Axel Saalbach, Hannes Nickisch
Can Pretrained Neural Networks Detect Anatomy? CoRR (2015)
Andrew Gordon Wilson, Christoph Dann, Hannes Nickisch
Thoughts on Massively Scalable Gaussian Processes. CoRR (2015)
Christoph H. Lampert, Hannes Nickisch, Stefan Harmeling
Attribute-Based Classification for Zero-Shot Visual Object Categorization. IEEE Trans. Pattern Anal. Mach. Intell. 36 (3) (2014)
Jürgen Weese, Alexandra Groth, Hannes Nickisch, Hans Barschdorf, Frank M. Weber, Jérôme Velut, M. 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
Generating anatomical models of the heart and the aorta from medical images for personalized physiological simulations. Medical Biol. Eng. Comput. 51 (11) (2013)
Pushmeet Kohli, Hannes Nickisch, Carsten Rother, Christoph Rhemann
User-Centric Learning and Evaluation of Interactive Segmentation Systems. Int. J. Comput. Vis. 100 (3) (2012)
Wendelin Böhmer, Steffen Grünewälder, Hannes Nickisch, Klaus Obermayer
Generating feature spaces for linear algorithms with regularized sparse kernel slow feature analysis. Mach. Learn. 89 (1-2) (2012)
Hannes Nickisch
glm-ie: Generalised Linear Models Inference & Estimation Toolbox. J. Mach. Learn. Res. 13 (2012)
Hannes Nickisch, Hans Barschdorf, Frank M. Weber, Martin W. Krueger, Olaf Dössel, Jürgen Weese
From Image to Personalized Cardiac Simulation: Encoding Anatomical Structures into a Model-Based Segmentation Framework. STACOM (2012)
Wendelin Böhmer, Steffen Grünewälder, Hannes Nickisch, Klaus Obermayer
Regularized Sparse Kernel Slow Feature Analysis. ECML/PKDD (1) (2011)
David Duvenaud, Hannes Nickisch, Carl Edward Rasmussen
Additive Gaussian Processes. NIPS (2011)
Matthias W. Seeger, Hannes Nickisch
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models. SIAM J. Imaging Sci. 4 (1) (2011)
Matthias W. Seeger, Hannes Nickisch
Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference. AISTATS (2011)
David Duvenaud, Hannes Nickisch, Carl Edward Rasmussen
Additive Gaussian Processes CoRR (2011)
Carl Edward Rasmussen, Hannes Nickisch
Gaussian Processes for Machine Learning (GPML) Toolbox. J. Mach. Learn. Res. 11 (2010)
Hannes Nickisch, Carl Edward Rasmussen
Gaussian Mixture Modeling with Gaussian Process Latent Variable Models. DAGM-Symposium (2010)
Hannes Nickisch, Carsten Rother, Pushmeet Kohli, Christoph Rhemann
Learning an interactive segmentation system. ICVGIP (2010)
Hannes Nickisch, Matthias W. Seeger
Convex variational Bayesian inference for large scale generalized linear models. ICML (2009)
Matthias W. Seeger, Hannes Nickisch
Large Scale Variational Inference and Experimental Design for Sparse Generalized Linear Models. Sampling-based Optimization in the Presence of Uncertainty (2009)
Hannes Nickisch, Pushmeet Kohli, Carsten Rother
Learning an Interactive Segmentation System CoRR (2009)
Christoph H. Lampert, Hannes Nickisch, Stefan Harmeling
Learning to detect unseen object classes by between-class attribute transfer. CVPR (2009)
Matthias W. Seeger, Hannes Nickisch
Compressed sensing and Bayesian experimental design. ICML (2008)
Matthias W. Seeger, Hannes Nickisch, Rolf Pohmann, Bernhard Schölkopf
Bayesian Experimental Design of Magnetic Resonance Imaging Sequences. NIPS (2008)

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Publication Activity (10 Years)

Top Topics

Top Venues

Hannes Nickisch