Attention Incorporated Network for Sharing Low-rank, Image and K-space Information during MR Image Reconstruction to Achieve Single Breath-hold Cardiac Cine Imaging.

[BibT_eX]

[DOI]

Siying Xu

Kerstin Hammernik

CoRR, 2024

Self-Supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representation.

[BibT_eX]

[DOI]

Francisco Sahli Costabal

Kerstin Hammernik

Claudia Prieto

Dimitrios C. Karampinos

Julia A. Schnabel

CoRR, 2024

Self-supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representations.

[BibT_eX]

[DOI]

Francisco Sahli Costabal

Kerstin Hammernik

Claudia Prieto

Dimitrios C. Karampinos

Julia A. Schnabel

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Physics-Informed Deep Learning for Motion-Corrected Reconstruction of Quantitative Brain MRI.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Direct Cardiac Segmentation from Undersampled K-Space using Transformers.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024

Neural Implicit k-space with Trainable Periodic Activation Functions for Cardiac MR Imaging.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2024, 2024

2023

Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging: Combining physics and machine learning for improved medical imaging.

[BibT_eX]

[DOI]

IEEE Signal Process. Mag., 2023

Reconstruction-driven motion estimation for motion-compensated MR CINE imaging.

[BibT_eX]

[DOI]

CoRR, 2023

Towards Generalised Neural Implicit Representations for Image Registration.

[BibT_eX]

[DOI]

Veronika A. Zimmer

Kerstin Hammernik

Vasiliki Sideri-Lampretsa

Proceedings of the Deep Generative Models - Third MICCAI Workshop, 2023

ICoNIK: Generating Respiratory-Resolved Abdominal MR Reconstructions Using Neural Implicit Representations in k-Space.

[BibT_eX]

[DOI]

Dimitrios C. Karampinos

Kerstin Hammernik

Julia A. Schnabel

Proceedings of the Deep Generative Models - Third MICCAI Workshop, 2023

The Challenge of Fetal Cardiac MRI Reconstruction Using Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the Perinatal, Preterm and Paediatric Image Analysis, 2023

Global k-Space Interpolation for Dynamic MRI Reconstruction Using Masked Image Modeling.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Propagation and Attribution of Uncertainty in Medical Imaging Pipelines.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2023

Physics-Aware Motion Simulation For T2*-Weighted Brain MRI.

[BibT_eX]

[DOI]

Proceedings of the Simulation and Synthesis in Medical Imaging, 2023

NISF: Neural Implicit Segmentation Functions.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Neural Implicit k-Space for Binning-Free Non-Cartesian Cardiac MR Imaging.

[BibT_eX]

[DOI]

Proceedings of the Information Processing in Medical Imaging, 2023

2022

Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction.

[BibT_eX]

[DOI]

IEEE Trans. Medical Imaging, 2022

Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging.

[BibT_eX]

[DOI]

CoRR, 2022

Differentially private training of residual networks with scale normalisation.

[BibT_eX]

[DOI]

CoRR, 2022

Embedding Gradient-Based Optimization in Image Registration Networks.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Learning-Based and Unrolled Motion-Compensated Reconstruction for Cardiac MR CINE Imaging.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022

Long-Term Cognitive Outcome Prediction in Stroke Patients Using Multi-task Learning on Imaging and Tabular Data.

[BibT_eX]

[DOI]

Proceedings of the Predictive Intelligence in Medicine - 5th International Workshop, 2022

2021

GraDIRN: Learning Iterative Gradient Descent-based Energy Minimization for Deformable Image Registration.

[BibT_eX]

[DOI]

CoRR, 2021

Complex-valued deep learning with differential privacy.

[BibT_eX]

[DOI]

CoRR, 2021

The Impact of Domain Shift on Left and Right Ventricle Segmentation in Short Axis Cardiac MR Images.

[BibT_eX]

[DOI]

Proceedings of the Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge, 2021

Quality-Aware Cine Cardiac MRI Reconstruction and Analysis from Undersampled K-Space Data.

[BibT_eX]

[DOI]

Miguel Castelo-Branco

Proceedings of the Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge, 2021

Learning Diffeomorphic and Modality-invariant Registration using B-splines.

[BibT_eX]

[DOI]

Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021

Efficient Image Registration Network for Non-Rigid Cardiac Motion Estimation.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning for Medical Image Reconstruction, 2021

Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning for Medical Image Reconstruction, 2021

Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation.

[BibT_eX]

[DOI]

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

Bias Field Robustness Verification of Large Neural Image Classifiers.

[BibT_eX]

[DOI]

Proceedings of the 32nd British Machine Vision Conference 2021, 2021

Motion-Guided Physics-Based Learning for Cardiac MRI Reconstruction.

[BibT_eX]

[DOI]

Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020

Deep-Learning Methods for Parallel Magnetic Resonance Imaging Reconstruction: A Survey of the Current Approaches, Trends, and Issues.

[BibT_eX]

[DOI]

IEEE Signal Process. Mag., 2020

CG-SENSE revisited: Results from the first ISMRM reproducibility challenge.

[BibT_eX]

[DOI]

CoRR, 2020

Deep Network Interpolation for Accelerated Parallel MR Image Reconstruction.

[BibT_eX]

[DOI]

CoRR, 2020

Deep-learning based motion-corrected image reconstruction in 4D magnetic resonance imaging of the body trunk.

[BibT_eX]

[DOI]

Proceedings of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2020

2019

Variationsnetzwerke für die medizinische Bildrekonstruktion.

[BibT_eX]

[DOI]

Kerstin Hammernik

Proceedings of the Ausgezeichnete Informatikdissertationen 2019., 2019

Σ-net: Systematic Evaluation of Iterative Deep Neural Networks for Fast Parallel MR Image Reconstruction.

[BibT_eX]

[DOI]

CoRR, 2019

Σ-net: Ensembled Iterative Deep Neural Networks for Accelerated Parallel MR Image Reconstruction.

[BibT_eX]

[DOI]

CoRR, 2019

Deep Learning Methods for Parallel Magnetic Resonance Image Reconstruction.

[BibT_eX]

[DOI]

CoRR, 2019

Joint Multi-anatomy Training of a Variational Network for Reconstruction of Accelerated Magnetic Resonance Image Acquisitions.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning for Medical Image Reconstruction, 2019

2018

Sparse-View CT Reconstruction Using Wasserstein GANs.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning for Medical Image Reconstruction, 2018

Variational Deep Learning for Low-Dose Computed Tomography.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017

Learning a Variational Network for Reconstruction of Accelerated MRI Data.

[BibT_eX]

[DOI]

CoRR, 2017

Variational Networks: Connecting Variational Methods and Deep Learning.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition - 39th German Conference, 2017

Trainable Regularization for Multi-frame Superresolution.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition - 39th German Conference, 2017

A Deep Learning Architecture for Limited-Angle Computed Tomography Reconstruction.

[BibT_eX]

[DOI]

Proceedings of the Bildverarbeitung für die Medizin 2017 - Algorithmen - Systeme, 2017

2016

A multi-center milestone study of clinical vertebral CT segmentation.

[BibT_eX]

[DOI]

Comput. Medical Imaging Graph., 2016

Learning joint demosaicing and denoising based on sequential energy minimization.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE International Conference on Computational Photography, 2016

2015

Automatic Intervertebral Disc Localization and Segmentation in 3D MR Images Based on Regression Forests and Active Contours.

[BibT_eX]

[DOI]

Proceedings of the Computational Methods and Clinical Applications for Spine Imaging, 2015

Kerstin Hammernik

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