Kerstin Hammernik

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 65

Top Topics

Image Reconstruction

Motion Estimation

Magnetic Resonance

Top Venues

IEEE Trans. Medical Imaging

Publications

Siying Xu, Kerstin Hammernik, Andreas Lingg, Jens Kübler, Patrick Krumm, Daniel Rueckert, Sergios Gatidis, Thomas Küstner
Attention Incorporated Network for Sharing Low-rank, Image and K-space Information during MR Image Reconstruction to Achieve Single Breath-hold Cardiac Cine Imaging. CoRR (2024)
Veronika Spieker, Hannah Eichhorn, Kerstin Hammernik, Daniel Rueckert, Christine Preibisch, Dimitrios C. Karampinos, Julia A. Schnabel
Deep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review. IEEE Trans. Medical Imaging 43 (2) (2024)
Aya Ghoul, Jiazhen Pan, Andreas Lingg, Jens Kübler, Patrick Krumm, Kerstin Hammernik, Daniel Rueckert, Sergios Gatidis, Thomas Küstner
Attention-Aware Non-Rigid Image Registration for Accelerated MR Imaging. IEEE Trans. Medical Imaging 43 (8) (2024)
Veronika Spieker, Hannah Eichhorn, Jonathan K. Stelter, Wenqi Huang, Rickmer F. Braren, Daniel Rückert, Francisco Sahli Costabal, Kerstin Hammernik, Claudia Prieto, Dimitrios C. Karampinos, Julia A. Schnabel
Self-Supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representation. CoRR (2024)
Jiazhen Pan, Manal Hamdi, Wenqi Huang, Kerstin Hammernik, Thomas Küstner, Daniel Rueckert
Unrolled and rapid motion-compensated reconstruction for cardiac CINE MRI. Medical Image Anal. 91 (2024)
Patrick T. Haft, Wenqi Huang, Gastão Cruz, Daniel Rueckert, Veronika A. Zimmer, Kerstin Hammernik
Neural Implicit k-space with Trainable Periodic Activation Functions for Cardiac MR Imaging. Bildverarbeitung für die Medizin (2024)
Inês Machado, Esther Puyol-Antón, Kerstin Hammernik, Gastão Cruz, Devran Ugurlu, Ihsane Olakorede, Ilkay Öksüz, Bram Ruijsink, Miguel Castelo-Branco, Alistair A. Young, Claudia Prieto, Julia A. Schnabel, Andrew P. King
A Deep Learning-Based Integrated Framework for Quality-Aware Undersampled Cine Cardiac MRI Reconstruction and Analysis. IEEE Trans. Biomed. Eng. 71 (3) (2024)
Jiazhen Pan, Wenqi Huang, Daniel Rueckert, Thomas Küstner, Kerstin Hammernik
Motion-Compensated MR CINE Reconstruction With Reconstruction-Driven Motion Estimation. IEEE Trans. Medical Imaging 43 (7) (2024)
Yundi Zhang, Nil Stolt Ansó, Jiazhen Pan, Wenqi Huang, Kerstin Hammernik, Daniel Rueckert
Direct Cardiac Segmentation from Undersampled K-space Using Transformers. CoRR (2024)
Aya Ghoul, Jiazhen Pan, Andreas Lingg, Jens Kübler, Patrick Krumm, Kerstin Hammernik, Daniel Rueckert, Sergios Gatidis, Thomas Küstner
Attention-aware non-rigid image registration for accelerated MR imaging. CoRR (2024)
Veronika Spieker, Hannah Eichhorn, Kerstin Hammernik, Daniel Rueckert, Christine Preibisch, Dimitrios C. Karampinos, Julia A. Schnabel
Deep Learning for Retrospective Motion Correction in MRI: A Comprehensive Review. CoRR (2023)
Denis Prokopenko, Kerstin Hammernik, Thomas A. Roberts, David F. A. Lloyd, Daniel Rueckert, Joseph V. Hajnal
The Challenge of Fetal Cardiac MRI Reconstruction Using Deep Learning. PIPPI@MICCAI (2023)
Leonhard F. Feiner, Martin J. Menten, Kerstin Hammernik, Paul Hager, Wenqi Huang, Daniel Rueckert, Rickmer F. Braren, Georgios Kaissis
Propagation and Attribution of Uncertainty in Medical Imaging Pipelines. UNSURE@MICCAI (2023)
Denis Prokopenko, Kerstin Hammernik, Thomas A. Roberts, David F. A Lloyd, Daniel Rueckert, Joseph V. Hajnal
The Challenge of Fetal Cardiac MRI Reconstruction Using Deep Learning. CoRR (2023)
Hannah Eichhorn, Kerstin Hammernik, Veronika Spieker, Samira M. Epp, Daniel Rueckert, Christine Preibisch, Julia A. Schnabel
Physics-Aware Motion Simulation For T2*-Weighted Brain MRI. SASHIMI@MICCAI (2023)
Veronika Spieker, Wenqi Huang, Hannah Eichhorn, Jonathan K. Stelter, Kilian Weiss, Veronika A. Zimmer, Rickmer F. Braren, Dimitrios C. Karampinos, Kerstin Hammernik, Julia A. Schnabel
ICoNIK: Generating Respiratory-Resolved Abdominal MR Reconstructions Using Neural Implicit Representations in k-Space. CoRR (2023)
Veronika Spieker, Wenqi Huang, Hannah Eichhorn, Jonathan K. Stelter, Kilian Weiss, Veronika A. Zimmer, Rickmer F. Braren, Dimitrios C. Karampinos, Kerstin Hammernik, Julia A. Schnabel
ICoNIK: Generating Respiratory-Resolved Abdominal MR Reconstructions Using Neural Implicit Representations in k-Space. DGM4MICCAI (2023)
Leonhard F. Feiner, Martin J. Menten, Kerstin Hammernik, Paul Hager, Wenqi Huang, Daniel Rueckert, Rickmer F. Braren, Georgios Kaissis
Propagation and Attribution of Uncertainty in Medical Imaging Pipelines. CoRR (2023)
Jiazhen Pan, Suprosanna Shit, Özgün Turgut, Wenqi Huang, Hongwei Bran Li, Nil Stolt Ansó, Thomas Küstner, Kerstin Hammernik, Daniel Rueckert
Global k-Space Interpolation for Dynamic MRI Reconstruction Using Masked Image Modeling. MICCAI (10) (2023)
Jiazhen Pan, Wenqi Huang, Daniel Rueckert, Thomas Küstner, Kerstin Hammernik
Reconstruction-driven motion estimation for motion-compensated MR CINE imaging. CoRR (2023)
Wenqi Huang, Hongwei Bran Li, Jiazhen Pan, Gastão Cruz, Daniel Rueckert, Kerstin Hammernik
Neural Implicit k-Space for Binning-Free Non-Cartesian Cardiac MR Imaging. IPMI (2023)
Kerstin Hammernik, Thomas Küstner, Burhaneddin Yaman, Zhengnan Huang, Daniel Rueckert, Florian Knoll, Mehmet Akçakaya
Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging: Combining physics and machine learning for improved medical imaging. IEEE Signal Process. Mag. 40 (1) (2023)
Veronika A. Zimmer, Kerstin Hammernik, Vasiliki Sideri-Lampretsa, Wenqi Huang, Anna Reithmeir, Daniel Rueckert, Julia A. Schnabel
Towards Generalised Neural Implicit Representations for Image Registration. DGM4MICCAI (2023)
Nil Stolt Ansó, Julian McGinnis, Jiazhen Pan, Kerstin Hammernik, Daniel Rueckert
NISF: Neural Implicit Segmentation Functions. MICCAI (4) (2023)
Jiazhen Pan, Suprosanna Shit, Özgün Turgut, Wenqi Huang, Hongwei Bran Li, Nil Stolt Ansó, Thomas Küstner, Kerstin Hammernik, Daniel Rueckert
Global k-Space Interpolation for Dynamic MRI Reconstruction using Masked Image Modeling. CoRR (2023)
Dominik Narnhofer, Alexander Effland, Erich Kobler, Kerstin Hammernik, Florian Knoll, Thomas Pock
Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction. IEEE Trans. Medical Imaging 41 (2) (2022)
Huaqi Qiu, Kerstin Hammernik, Chen Qin, Chen Chen, Daniel Rueckert
Embedding Gradient-Based Optimization in Image Registration Networks. MICCAI (6) (2022)
Jiazhen Pan, Daniel Rueckert, Thomas Küstner, Kerstin Hammernik
Learning-Based and Unrolled Motion-Compensated Reconstruction for Cardiac MR CINE Imaging. MICCAI (6) (2022)
Kerstin Hammernik, Thomas Küstner, Burhaneddin Yaman, Zhengnan Huang, Daniel Rueckert, Florian Knoll, Mehmet Akçakaya
Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging. CoRR (2022)
Moritz Binzer, Kerstin Hammernik, Daniel Rueckert, Veronika A. Zimmer
Long-Term Cognitive Outcome Prediction in Stroke Patients Using Multi-task Learning on Imaging and Tabular Data. PRIME@MICCAI (2022)
Jiazhen Pan, Daniel Rueckert, Thomas Küstner, Kerstin Hammernik
Learning-based and unrolled motion-compensated reconstruction for cardiac MR CINE imaging. CoRR (2022)
Wenqi Huang, Hongwei Li, Gastão Cruz, Jiazhen Pan, Daniel Rueckert, Kerstin Hammernik
Neural Implicit k-Space for Binning-free Non-Cartesian Cardiac MR Imaging. CoRR (2022)
Helena Klause, Alexander Ziller, Daniel Rueckert, Kerstin Hammernik, Georgios Kaissis
Differentially private training of residual networks with scale normalisation. CoRR (2022)
Inês Prata Machado, Esther Puyol-Antón, Kerstin Hammernik, Gastão Cruz, Devran Ugurlu, Ihsane Olakorede, Ilkay Öksüz, Bram Ruijsink, Miguel Castelo-Branco, Alistair A. Young, Claudia Prieto, Julia A. Schnabel, Andrew P. King
A Deep Learning-based Integrated Framework for Quality-aware Undersampled Cine Cardiac MRI Reconstruction and Analysis. CoRR (2022)
Huaqi Qiu, Chen Qin, Andreas Schuh, Kerstin Hammernik, Daniel Rueckert
Learning Diffeomorphic and Modality-invariant Registration using B-splines. MIDL (2021)
Inês Machado, Esther Puyol-Antón, Kerstin Hammernik, Gastão Cruz, Devran Ugurlu, Bram Ruijsink, Miguel Castelo-Branco, Alistair A. Young, Claudia Prieto, Julia A. Schnabel, Andrew P. King
Quality-Aware Cine Cardiac MRI Reconstruction and Analysis from Undersampled K-Space Data. STACOM@MICCAI (2021)
Patricia M. Johnson, Geunu Jeong, Kerstin Hammernik, Jo Schlemper, Chen Qin, Jinming Duan, Daniel Rueckert, Jingu Lee, Nicola Pezzotti, Elwin de Weerdt, Sahar Yousefi, Mohamed S. Elmahdy, Jeroen Hendrikus Franciscus Van Gemert, Christophe Schülke, Mariya Doneva, Tim Nielsen, Sergey Kastryulin, Boudewijn P. F. Lelieveldt, Matthias J. P. van Osch, Marius Staring, Eric Z. Chen, Puyang Wang, Xiao Chen, Terrence Chen, Vishal M. Patel, Shanhui Sun, Hyungseob Shin, Yohan Jun, Taejoon Eo, Sewon Kim, Taeseong Kim, Dosik Hwang, Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan W. A. Caan, Max Welling, Matthew J. Muckley, Florian Knoll
Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge. MLMIR@MICCAI (2021)
Dominik Narnhofer, Alexander Effland, Erich Kobler, Kerstin Hammernik, Florian Knoll, Thomas Pock
Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction. CoRR (2021)
Devran Ugurlu, Esther Puyol-Antón, Bram Ruijsink, Alistair A. Young, Inês Machado, Kerstin Hammernik, Andrew P. King, Julia A. Schnabel
The Impact of Domain Shift on Left and Right Ventricle Segmentation in Short Axis Cardiac MR Images. CoRR (2021)
Chen Chen, Kerstin Hammernik, Cheng Ouyang, Chen Qin, Wenjia Bai, Daniel Rueckert
Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation. CoRR (2021)
Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Kerstin Hammernik, Daniel Rueckert, Georgios Kaissis
Complex-valued deep learning with differential privacy. CoRR (2021)
Patrick Henriksen, Kerstin Hammernik, Daniel Rueckert, Alessio Lomuscio
Bias Field Robustness Verification of Large Neural Image Classifiers. BMVC (2021)
Jiazhen Pan, Daniel Rueckert, Thomas Küstner, Kerstin Hammernik
Efficient Image Registration Network for Non-Rigid Cardiac Motion Estimation. MLMIR@MICCAI (2021)
Devran Ugurlu, Esther Puyol-Antón, Bram Ruijsink, Alistair A. Young, Inês Machado, Kerstin Hammernik, Andrew P. King, Julia A. Schnabel
The Impact of Domain Shift on Left and Right Ventricle Segmentation in Short Axis Cardiac MR Images. STACOM@MICCAI (2021)
Huaqi Qiu, Kerstin Hammernik, Chen Qin, Daniel Rueckert
GraDIRN: Learning Iterative Gradient Descent-based Energy Minimization for Deformable Image Registration. CoRR (2021)
Chen Chen, Kerstin Hammernik, Cheng Ouyang, Chen Qin, Wenjia Bai, Daniel Rueckert
Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation. MICCAI (3) (2021)
Kerstin Hammernik, Jiazhen Pan, Daniel Rueckert, Thomas Küstner
Motion-Guided Physics-Based Learning for Cardiac MRI Reconstruction. ACSCC (2021)
Inês Machado, Esther Puyol-Antón, Kerstin Hammernik, Gastão Cruz, Devran Ugurlu, Bram Ruijsink, Miguel Castelo-Branco, Alistair A. Young, Claudia Prieto, Julia A. Schnabel, Andrew P. King
Quality-aware Cine Cardiac MRI Reconstruction and Analysis from Undersampled k-space Data. CoRR (2021)
Oliver Maier, Steven H. Baete, Alexander Fyrdahl, Kerstin Hammernik, Seb Harrevelt, Lars Kasper, Agah Karakuzu, Michael Loecher, Franz Patzig, Ye Tian, Ke Wang, Daniel Gallichan, Martin Uecker, Florian Knoll
CG-SENSE revisited: Results from the first ISMRM reproducibility challenge. CoRR (2020)
Florian Knoll, Kerstin Hammernik, Chi Zhang, Steen Moeller, Thomas Pock, Daniel K. Sodickson, Mehmet Akçakaya
Deep-Learning Methods for Parallel Magnetic Resonance Imaging Reconstruction: A Survey of the Current Approaches, Trends, and Issues. IEEE Signal Process. Mag. 37 (1) (2020)
Thomas Küstner, Jiazhen Pan, Christopher Gilliam, Haikun Qi, Gastão Cruz, Kerstin Hammernik, Bin Yang, Thierry Blu, Daniel Rueckert, René M. Botnar, Claudia Prieto, Sergios Gatidis
Deep-learning based motion-corrected image reconstruction in 4D magnetic resonance imaging of the body trunk. APSIPA (2020)
Chen Qin, Jo Schlemper, Kerstin Hammernik, Jinming Duan, Ronald M. Summers, Daniel Rueckert
Deep Network Interpolation for Accelerated Parallel MR Image Reconstruction. CoRR (2020)
Kerstin Hammernik, Jo Schlemper, Chen Qin, Jinming Duan, Ronald M. Summers, Daniel Rueckert
Σ-net: Systematic Evaluation of Iterative Deep Neural Networks for Fast Parallel MR Image Reconstruction. CoRR (2019)
Patricia M. Johnson, Matthew J. Muckley, Mary Bruno, Erich Kobler, Kerstin Hammernik, Thomas Pock, Florian Knoll
Joint Multi-anatomy Training of a Variational Network for Reconstruction of Accelerated Magnetic Resonance Image Acquisitions. MLMIR@MICCAI (2019)
Florian Knoll, Kerstin Hammernik, Chi Zhang, Steen Moeller, Thomas Pock, Daniel K. Sodickson, Mehmet Akçakaya
Deep Learning Methods for Parallel Magnetic Resonance Image Reconstruction. CoRR (2019)
Jo Schlemper, Chen Qin, Jinming Duan, Ronald M. Summers, Kerstin Hammernik
Σ-net: Ensembled Iterative Deep Neural Networks for Accelerated Parallel MR Image Reconstruction. CoRR (2019)
Franz Thaler, Kerstin Hammernik, Christian Payer, Martin Urschler, Darko Stern
Sparse-View CT Reconstruction Using Wasserstein GANs. MLMIR@MICCAI (2018)
Erich Kobler, Matthew J. Muckley, Baiyu Chen, Florian Knoll, Kerstin Hammernik, Thomas Pock, Daniel K. Sodickson, Ricardo Otazo
Variational Deep Learning for Low-Dose Computed Tomography. ICASSP (2018)
Kerstin Hammernik, Tobias Würfl, Thomas Pock, Andreas K. Maier
A Deep Learning Architecture for Limited-Angle Computed Tomography Reconstruction. Bildverarbeitung für die Medizin (2017)
Kerstin Hammernik, Teresa Klatzer, Erich Kobler, Michael P. Recht, Daniel K. Sodickson, Thomas Pock, Florian Knoll
Learning a Variational Network for Reconstruction of Accelerated MRI Data. CoRR (2017)
Teresa Klatzer, Daniel Soukup, Erich Kobler, Kerstin Hammernik, Thomas Pock
Trainable Regularization for Multi-frame Superresolution. GCPR (2017)
Erich Kobler, Teresa Klatzer, Kerstin Hammernik, Thomas Pock
Variational Networks: Connecting Variational Methods and Deep Learning. GCPR (2017)
Jianhua Yao, Joseph E. Burns, Daniel Forsberg, Alexander Seitel, Abtin Rasoulian, Purang Abolmaesumi, Kerstin Hammernik, Martin Urschler, Bulat Ibragimov, Robert Korez, Tomaz Vrtovec, Isaac Castro-Mateos, Jose M. Pozo, Alejandro F. Frangi, Ronald M. Summers, Shuo Li
A multi-center milestone study of clinical vertebral CT segmentation. Comput. Medical Imaging Graph. 49 (2016)
Teresa Klatzer, Kerstin Hammernik, Patrick Knöbelreiter, Thomas Pock
Learning joint demosaicing and denoising based on sequential energy minimization. ICCP (2016)
Martin Urschler, Kerstin Hammernik, Thomas Ebner, Darko Stern
Automatic Intervertebral Disc Localization and Segmentation in 3D MR Images Based on Regression Forests and Active Contours. CSI@MICCAI (2015)