Hannes Nickisch

55 papers A* 6A 2B 5Journal 24Unranked 17

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