@Article{jaeckle2021IJERPH,
AUTHOR = {Jäckle, Sonja and Röger, Elias and Dicken, Volker and Geisler, Benjamin and Schumacher, Jakob and Westphal, Max},
TITLE = {A Statistical Model to Assess Risk for Supporting COVID-19 Quarantine Decisions},
JOURNAL = {International Journal of Environmental Research and Public Health},
VOLUME = {18},
YEAR = {2021},
NUMBER = {17},
ARTICLE-NUMBER = {9166},
URL = {https://www.mdpi.com/1660-4601/18/17/9166},
ISSN = {1660-4601},
ABSTRACT = {In Germany, local health departments are responsible for surveillance of the current pandemic situation. One of their major tasks is to monitor infected persons. For instance, the direct contacts of infectious persons at group meetings have to be traced and potentially quarantined. Such quarantine requirements may be revoked, when all contact persons obtain a negative polymerase chain reaction (PCR) test result. However, contact tracing and testing is time-consuming, costly and not always feasible. In this work, we present a statistical model for the probability that no transmission of COVID-19 occurred given an arbitrary number of negative test results among contact persons. Hereby, the time-dependent sensitivity and specificity of the PCR test are taken into account. We employ a parametric Bayesian model which combines an adaptable Beta-Binomial prior and two likelihood components in a novel fashion. This is illustrated for group events in German school classes. The first evaluation on a real-world dataset showed that our approach can support important quarantine decisions with the goal to achieve a better balance between necessary containment of the pandemic and preservation of social and economic life. Future work will focus on further refinement and evaluation of quarantine decisions based on our statistical model.},
DOI = {10.3390/ijerph18179166}
}

@article{jaeckle2021CURAC,
author = {Sonja Jäckle and Tim Eixmann and Florian Matysiak and Malte Maria Sieren and Marco Horn and Hinnerk Schulz-Hildebrandt and Gereon Hüttmann and Torben Pätz},
doi = {doi:10.1515/cdbme-2021-1004},
url = {https://doi.org/10.1515/cdbme-2021-1004},
title = {3D Stent Graft Guidance based on Tracking Systems for Endovascular Aneurysm Repair},
journal = {Current Directions in Biomedical Engineering},
number = {1},
volume = {7},
year = {2021},
keywords={NavEVAR},
pages = {17--20}
}

@phdthesis{jackle2021guidance,
  title={Guidance of medical instruments based on tracking systems},
  author={Sonja J{\"a}ckle},
  year={2021},
  school={Jacobs University Bremen}
}

@article{jaeckle2021IJMRCAS,
author = {Jäckle, Sonja and Lange, Annkristin and García-Vázquez, Verónica and Eixmann, Tim and Matysiak, Florian and Sieren, Malte Maria and Horn, Marco and Schulz-Hildebrandt, Hinnerk and Hüttmann, Gereon and Ernst, Floris and Heldmann, Stefan and Pätz, Torben and Preusser, Tobias},
title = {Instrument localisation for endovascular aneurysm repair: Comparison of two methods based on tracking systems or using imaging},
journal = {The International Journal of Medical Robotics and Computer Assisted Surgery},
volume = {17},
number = {6},
pages = {e2327},
year = {2021},
keyword = {NavEVAR}
}

@Proceedings{Lellmann2021,
  title  = {Journal of Mathematical Imaging and Vision, Special Issue on Scale Space and Variational Methods in Computer Vision},
  year   = {2021},
  author = {Lellmann, J. and Modersitzki, J.},
}

@Article{Diepeveen2021,
  author  = {Diepeveen, W. and Lellmann, J.},
  title   = {An Inexact Semismooth {Newton} Method on {Riemannian} Manifolds with Application to Duality-Based Total Variation Denoising},
  journal = {{SIAM} Journal on Imaging Sciences},
  year    = {2021},
  volume  = {14},
  number  = {4},
  pages   = {1565--1600},
}

@article{Homeyer2021, 
doi={10.4103/jpi.jpi_84_20}, 
url={https://doi.org/10.4103%2Fjpi.jpi_84_20}, 
year={2021}, 
publisher={Elsevier {BV}}, 
volume={12}, 
number={1}, 
pages={13}, 
author={Homeyer, André and Lotz, Johannes and Schwen, Lars Ole and Weiss, Nick and Romberg, Daniel and Höfener, Henning and Zerbe, Norman and Hufnagl, Peter}, 
title={Artificial intelligence in pathology: From prototype to product}, 
journal={Journal of Pathology Informatics}
}

@article{hering2021learn2reg,
  title={Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning},
  author={Hering, Alessa and Hansen, Lasse and Mok, Tony CW and Chung, Albert and Siebert, Hanna and H{\"a}ger, Stephanie and Lange, Annkristin and Kuckertz, Sven and Heldmann, Stefan and Shao, Wei and others},
  journal={arXiv preprint arXiv:2112.04489},
  year={2021}
}

@inproceedings{hering2021fraunhofer,
  title={Fraunhofer MEVIS Image Registration Solutions for the Learn2Reg 2021 Challenge},
  author={Hering, Alessa and Lange, Annkristin and Heldmann, Stefan and H{\"a}ger, Stephanie and Kuckertz, Sven},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={147--152},
  year={2021},
  organization={Springer}
}

@inproceedings{hering2021whole,
  title={Whole-Body Soft-Tissue Lesion Tracking and Segmentation in Longitudinal CT Imaging Studies},
  author={Hering, Alessa and Peisen, Felix and Amaral, Teresa and Gatidis, Sergios and Eigentler, Thomas and Othman, Ahmed and Moltz, Jan Hendrik},
  booktitle={Medical Imaging with Deep Learning},
  pages={312--326},
  year={2021},
  organization={PMLR}
}

@article{hering2021cnn,
  title={CNN-based lung CT registration with multiple anatomical constraints},
  author={Hering, Alessa and H{\"a}ger, Stephanie and Moltz, Jan and Lessmann, Nikolas and Heldmann, Stefan and van Ginneken, Bram},
  journal={Medical Image Analysis},
  volume={72},
  pages={102139},
  year={2021},
  publisher={Elsevier}
}

@article{roth2021rapid,
  title={Rapid artificial intelligence solutions in a pandemic-the COVID-19-20 lung CT lesion segmentation challenge},
  author={Roth, Holger R and Xu, Ziyue and Diez, Carlos Tor and Jacob, Ramon Sanchez and Zember, Jonathan and Molto, Jose and Li, Wenqi and Xu, Sheng and Turkbey, Baris and Turkbey, Evrim and others},
  journal={Research Square},
  year={2021},
  publisher={American Journal Experts}
}

@Article{Mannel4,
Author={{Mannel, Florian}},
Title={{On the order of convergence of Broyden’s method}},
FJournal={{Calcolo}},
Journal={{Calcolo}},
Volume={58},
Number={4},
Pages={1--21},
Year={2021},
Language={English},
doi={10.1007/s10092-021-00441-6},
}

@article{krenzlin2021decreased,
  title={Decreased superoxide dismutase concentrations (SOD) in plasma and CSF and increased circulating total antioxidant capacity (TAC) are associated with unfavorable neurological outcome after aneurysmal subarachnoid hemorrhage},
  author={Krenzlin, Harald and Wesp, Dominik and Schmitt, Jan and Frenz, Christina and Kurz, Elena and Masomi-Bornwasser, Julia and Lotz, Johannes and Ringel, Florian and Kerz, Thomas and Keric, Naureen},
  journal={Journal of Clinical Medicine},
  volume={10},
  number={6},
  pages={1188},
  year={2021},
  publisher={MDPI}
}

@article{masomi2021influence,
  title={The influence of oxidative stress on neurological outcomes in spontaneous intracerebral hemorrhage},
  author={Masomi-Bornwasser, Julia and Kurz, Elena and Frenz, Christina and Schmitt, Jan and Wesp, Dominik MA and K{\"o}nig, Jochem and Lotz, Johannes and Ringel, Florian and Kerz, Thomas and Krenzlin, Harald and others},
  journal={Biomolecules},
  volume={11},
  number={11},
  pages={1615},
  year={2021},
  publisher={MDPI}
}

@article{iuga2021automated,
  title={Automated mapping and N-Staging of thoracic lymph nodes in contrast-enhanced CT scans of the chest using a fully convolutional neural network},
  author={Iuga, Andra-Iza and Lossau, Tanja and Caldeira, Liliana Laurenco and Rinneburger, Miriam and Lennartz, Simon and Hokamp, Nils Gro{\ss}e and P{\"u}sken, Michael and Carolus, Heike and Maintz, David and Klinder, Tobias and others},
  journal={European Journal of Radiology},
  volume={139},
  pages={109718},
  year={2021},
  publisher={Elsevier}
}

@Article{CoronaLellmannNestorEtAl2020,
  author =  {Corona, V. and Lellmann, J. and Nestor, P. and Sch\"onlieb, C.-B. and Acosta-Cabronero, J.},
  title =   {A multi-contrast MRI approach to thalamus segmentation},
  journal = {Human Brain Mapping},
  year =    {2020}
}

@incollection{PolzinEtAl2020DiscretizeOptimize,
title = "A discretize–optimize approach for LDDMM registration",
editor = "Xavier Pennec and Stefan Sommer and Tom Fletcher",
booktitle = "Riemannian Geometric Statistics in Medical Image Analysis",
publisher = "Academic Press",
pages = "479 - 532",
year = "2020",
isbn = "978-0-12-814725-2",
doi = "https://doi.org/10.1016/B978-0-12-814725-2.00022-4",
url = "http://www.sciencedirect.com/science/article/pii/B9780128147252000224",
author = "Thomas Polzin and Marc Niethammer and François-Xavier Vialard and Jan Modersitzki",
keywords = "LDDMM, Discretize–Optimize, Image Registration, Optimal Control, Lung, Computed Tomography, Runge–Kutta Methods",
abstract = " Large deformation diffeomorphic metric mapping (LDDMM) is a popular approach for deformable image registration with nice mathematical properties. LDDMM encodes spatial deformations through time-varying velocity fields. Hence registration requires optimization over these time-varying velocity fields, resulting in a large-scale constrained optimization problem. Typical numerical solution approaches for LDDMM use an optimize–discretize strategy, where optimality conditions are derived in the continuum and subsequently discretized and solved. Here we explore solution methods based on the discretize–optimize approach and discuss ramifications for popular LDDMM relaxation and shooting approaches. The focus is on a consistent method that uses the appropriate Runge–Kutta methods for the solution of all arising PDEs in the Eulerian frame. Additionally, we discuss both run-time and memory consumption requirements and present an approach that makes the registration suitable for standard PCs. We demonstrate the practicality of our proposed approach in the context of image registration applied to 3D computed tomography (CT) scans of the lung."
}

@phdthesis{2020-PhD-Vogt,
  Author = {Thomas Vogt},
  Title = {Measure-Valued Variational Models with Applications in Image Processing},
  School = {Institute of Mathematics and Image Computing, University of L\"ubeck},
  Year = {2020},
}

@inproceedings{jaeckle2020SPIE,
author = {Jäckle, Sonja and García-Vázquez, Verónica and von Haxthausen, Felix and Eixmann, Tim and Sieren, Malte Maria and Schulz-Hildebrandt, Hinnerk and Hüttmann, Gereon and Ernst, Floris and Kleemann, Markus and Paetz, Torben },
title = {{3D catheter guidance including shape sensing for endovascular navigation}},
volume = {11315},
booktitle = {Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling},
editor = {Baowei Fei and Cristian A. Linte},
organization = {International Society for Optics and Photonics},
publisher = {SPIE},
pages = {21 -- 29},
keywords = {catheter guidance, electromagnetic tracking, fiber Bragg gratings, shape sensing, endovascular navigation, endovascular aneurysm repair, NavEVAR},
year = {2020},
doi = {10.1117/12.2548094},
URL = {https://doi.org/10.1117/12.2548094}
}

@incollection{jaeckle2020BVM_FOSS,
  title={Abstract: Fiber Optical Shape Sensing of Flexible Instruments},
  author={J{\"a}ckle, Sonja and Eixmann, Tim and Schulz-Hildebrandt, Hinnerk and H{\"u}ttmann, Gereon and P{\"a}tz, Torben},
  booktitle={Bildverarbeitung f{\"u}r die Medizin 2020},
  pages={314--314},
  year={2020},
  keywords={NavEVAR},
  url={https://link.springer.com/chapter/10.1007/978-3-658-29267-6_70},
  doi={10.1007/978-3-658-29267-6_70},
  publisher={Springer}
}

@incollection{jaeckle20203BVM_3DCatheter,
  title={Abstract: 3D Catheter Guidance Including Shape Sensing for Endovascular Navigation},
  author={J{\"a}ckle, Sonja and Garc\'ia-V{\'a}zquez, Ver{\'o}nica and von Haxthausen, Felix and Eixmann, Tim and Sieren, Malte Maria and Schulz-Hildebrandt, Hinnerk and H{\"u}ttmann, Gereon and Ernst, Floris and Kleemann, Markus and P{\"a}tz, Torben},
  booktitle={Bildverarbeitung f{\"u}r die Medizin 2020},
  pages={261--261},
  year={2020},
  doi={10.1007/978-3-658-29267-6_58},
  url={https://link.springer.com/chapter/10.1007/978-3-658-29267-6_58},
  keywords={NavEVAR},
  publisher={Springer}
}

@incollection{lange2020intensity,
  title={Intensity-Based 2D-3D Registration Using Normalized Gradient Fields},
  author={Lange, Annkristin and Heldmann, Stefan},
  booktitle={Bildverarbeitung f{\"u}r die Medizin 2020},
  pages={163--168},
  year={2020},
  keywords={NavEVAR},
  url={https://doi.org/10.1007/978-3-658-29267-6_33},
  publisher={Springer}
}

@article{jaeckle2020IJCARS,
author = {Jäckle, Sonja and García-Vázquez, Verónica and Eixmann, Tim and Matysiak, Florian and von Haxthausen, Felix, and Sieren, Malte Maria and Schulz-Hildebrandt, Hinnerk and Hüttmann, Gereon and Ernst, Floris and Kleemann, Markus and Paetz, Torben },
title = {{Three-dimensional guidance including shape sensing of a stentgraft system for endovascular aneurysm repair}},
journal={International Journal of Computer Assisted Radiology and Surgery},
year={2020},
keywords = {NavEVAR},
url={https://doi.org/10.1007/s11548-020-02167-2},
}

@phdthesis{2020-PhD-Lotz,
  Author = {Johannes Lotz},
  Title = {Combined Local and Global Image Registration and its Application to Large-Scale Images in Digital Pathology},
  School = {Institute of Mathematics and Image Computing, University of Lübeck},
  Year = {2020},
}

@inproceedings{kuckertz2020SPIE,
  title={Deep learning based CT-CBCT image registration for adaptive radio therapy},
  author={Kuckertz, Sven and Papenberg, Nils and Honegger, Jonas and Morgas, Tomasz and Haas, Benjamin and Heldmann, Stefan},
  booktitle={Medical Imaging 2020: Image Processing},
  volume={11313},
  pages={113130Q},
  year={2020},
  organization={International Society for Optics and Photonics},
  url={http://dx.doi.org/10.1117%2F12.2549531}
}

@inproceedings{lange2020multilevel,
  title={Multilevel 2D-3D Intensity-Based Image Registration},
  author={Lange, Annkristin and Heldmann, Stefan},
  booktitle={International Workshop on Biomedical Image Registration},
  pages={57--66},
  year={2020},
  organization={Springer},
  keywords={NavEVAR},
  url={https://doi.org/10.1007/978-3-030-50120-4_6}
}

@InProceedings{kuckertz2020BVM,
author={Kuckertz, Sven and Papenberg, Nils and Honegger, Jonas and Morgas, Tomasz and Haas, Benjamin and Heldmann, Stefan},
editor={Tolxdorff, Thomas and Deserno, Thomas M. and Handels, Heinz and Maier, Andreas and Maier-Hein, Klaus H. and Palm, Christoph},
title={Abstract: Deep Learning Based CT-CBCT Image Registration for Adaptive Radio Therapy},
booktitle={Bildverarbeitung f{\"u}r die Medizin 2020},
year={2020},
publisher={Springer},
pages={229--229},
isbn={978-3-658-29267-6},
url={https://doi.org/10.1007/978-3-658-29267-6_51}
}

@inproceedings{kuckertz2020WBIR,
  title={Learning Deformable Image Registration with Structure Guidance Constraints for Adaptive Radiotherapy},
  author={Kuckertz, Sven and Papenberg, Nils and Honegger, Jonas and Morgas, Tomasz and Haas, Benjamin and Heldmann, Stefan},
  booktitle={International Workshop on Biomedical Image Registration},
  pages={44--53},
  year={2020},
  organization={Springer},
  url={http://dx.doi.org/10.1007%2F978-3-030-50120-4_5}
}

@inproceedings{Lotz2020ISBI,
  author={Mercan, C. and Mooij, G.C.A.M. and Tellez, D. and Lotz, J. and Weiss, N. and van Gerven, M. and Ciompi, F.},
  title={Virtual Staining for Mitosis Detection in Breast Histopathology},
  journal={2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)},
  publisher={IEEE}
  year={2020},
  url={https://doi.org/10.1109/isbi45749.2020.9098409},
}

@article{garcia2020catheter,
  title={Catheter pose-dependent virtual angioscopy images for endovascular aortic repair: validation with a video graphics array (VGA) camera},
  author={García-Vázquez, Verónica and Matysiak, Florian and Jäckle, Sonja and Eixmann, Tim and Sieren, Malte Maria and von Haxthausen, Felix and Ernst, Floris},
  journal={Current Directions in Biomedical Engineering},
  volume={6},
  number={1},
  year={2020},
  keywords={NavEVAR},
  publisher={De Gruyter}
}

@inproceedings{Aggrawal2020WBIR,
author={Aggrawal, Hari Om and Andersen, Martin S. and Modersitzki, Jan},
title={An Image Registration Framework for Discontinuous Mappings Along Cracks},
booktitle={International Workshop on Biomedical Image Registration},
year={2020},
publisher={Springer},
pages={163--173},
url={{{https://doi.org/10.1007/978-3-030-50120-4_16}}},
doi={{{10.1007/978-3-030-50120-4_16}}}
}

@inproceedings{Aggrawal2020ISBI,
author={Aggrawal, Hari Om and Modersitzki, Jan},
title={Accelerating the Registration of Image Sequences by Spatio-Temporal Multilevel Strategies},
booktitle={Proceedings - International Symposium on Biomedical Imaging},
year={2020},
publisher={IEEE Computer Society},
pages={683--686},
url={{{https://doi.org/10.1109/ISBI45749.2020.9098520}}},
doi={{{10.1109/ISBI45749.2020.9098520}}}
}

@Article{ParisottoLellmannMasnouSchoenlieb2020,
  author  = {Parisotto, S. and Lellmann, J. and Masnou, S. and Sch{\"o}nlieb, C.},
  title   = {Higher-Order Total Directional Variation: Imaging Applications},
  journal = {{SIAM} Journal on Imaging Sciences},
  year    = {2020},
  volume  = {13},
  number  = {4},
  pages   = {2063--2104},
}

@inproceedings{hager2020variable,
  title={Variable fraunhofer MEVIS RegLib comprehensively applied to Learn2Reg challenge},
  author={H{\"a}ger, Stephanie and Heldmann, Stefan and Hering, Alessa and Kuckertz, Sven and Lange, Annkristin},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={74--79},
  year={2020},
  organization={Springer}
}

@article{sieren2020rapid,
  title={Rapid study assessment in follow-up whole-body computed tomography in patients with multiple myeloma using a dedicated bone subtraction software},
  author={Sieren, MM and Brenne, F and Hering, A and Kienapfel, H and Gebauer, N and Oechtering, TH and F{\"u}rschke, A and Wegner, F and Stahlberg, E and Heldmann, S and others},
  journal={European Radiology},
  volume={30},
  number={6},
  pages={3198--3209},
  year={2020},
  publisher={Springer}
}

@article{lassen2020automatic,
  title={Automatic segmentation of the pulmonary lobes with a 3D u-net and optimized loss function},
  author={Lassen-Schmidt, Bianca and Hering, Alessa and Krass, Stefan and Meine, Hans},
  journal={arXiv preprint arXiv:2006.00083},
  year={2020}
}

@article{vogt2020connection,
  title={On the connection between dynamical optimal transport and functional lifting},
  author={Vogt, Thomas and Haase, Roland and Bednarski, Danielle and Lellmann, Jan},
  journal={arXiv preprint arXiv:2007.02587},
  year={2020}
}

@incollection{polzin2020discretize,
  title={A discretize--optimize approach for LDDMM registration},
  author={Polzin, Thomas and Niethammer, Marc and Vialard, Fran{\c{c}}ois-Xavier and Modersitzki, Jan},
  booktitle={Riemannian Geometric Statistics in Medical Image Analysis},
  pages={479--532},
  year={2020},
  publisher={Elsevier}
}

@inproceedings{chen2020localization,
  title={Localization of endovascular tools in X-ray images using a motorized C-arm: visualization on HoloLens},
  author={Chen, Yenjung and Shah, Nilay Yatinkumar and Goswami, Subhra Sundar and Lange, Annkristin and Von Haxthausen, Felix and Sieren, Malte Maria and Hagenah, Jannis and Ernst, Floris and Garc{\'\i}a-V{\'a}zquez, Ver{\'o}nica},
  booktitle={Current Directions in Biomedical Engineering},
  volume={6},
  number={1},
  pages={20200029},
  year={2020},
  organization={De Gruyter}
}

@article{jaeckle2019FOSS,
  author={J{\"a}ckle, Sonja and Eixmann, Tim and Schulz-Hildebrandt, Hinnerk and H{\"u}ttmann, Gereon and P{\"a}tz, Torben},
  title={Fiber optical shape sensing of flexible instruments for endovascular navigation},
  journal={International Journal of Computer Assisted Radiology and Surgery},
  year={2019},
  volume={14},
  number={12},
  pages={2137--2145},
  keywords = {NavEVAR},
  url={https://doi.org/10.1007/s11548-019-02059-0},
}

@inproceedings{VogtLellmann2019,
author={Vogt, Thomas and Lellmann, Jan},
title={Functional Liftings of Vectorial Variational Problems with Laplacian Regularization},
booktitle={Scale Space and Variational Methods in Computer Vision: 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30-July 4, 2019, Proceedings},
year={2019},
editor={Burger, Martin and Lellmann, Jan and Modersitzki, Jan},
publisher={Springer International Publishing},
pages={559--571},
url={{{https://arxiv.org/pdf/1904.00898.pdf}}},
doi={{{10.1007/978-3-030-22368-7_44}}}
}

@inproceedings{Brehmer2019,
author={Brehmer, Kai and Aggrawal, Hari Om and Heldmann, Stefan and Modersitzki, Jan},
title={Variational registration of multiple images with the SVD based SqN distance measure},
booktitle={Scale Space and Variational Methods in Computer Vision: 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30-July 4, 2019, Proceedings},
year={2019},
editor={Burger, Martin and Lellmann, Jan and Modersitzki, Jan},
publisher={Springer International Publishing},
pages={251--262},
url={{{https://arxiv.org/abs/1907.09732}}},
doi={{{10.1007/978-3-030-22368-7_20}}}
}

@article{Wacker2019,
  title={Two variants of magnetic diffusivity stabilized finite element methods for the magnetic induction equation},
  author={Wacker, Benjamin},
  journal={Mathematical Methods in the Applied Sciences},
  year={2019},
  publisher={Wiley Online Library}
}

@incollection{VogtEtAl2019,
author={Vogt, Thomas and Strekalovskiy, Evgeny and Cremers, Daniel and Lellmann, Jan},
title={Lifting methods for manifold-valued variational problems},
series={Springer Handbooks},
booktitle={Variational Methods for Nonlinear Geometric Data and Applications},
editor={Grohs, Philipp and Holler, Martin and Weinmann, Andreas},
publisher={Springer International Publishing},
pages={In press},
year={2019},
url={{{https://arxiv.org/pdf/1908.03776.pdf}}},
doi={{{10.1007/tba}}}
}

@INPROCEEDINGS{vonHaxthausen2019,
    author = {von Haxthausen, Felix and J{\"{a}}ckle, Sonja and Strehlow, Jan and Ernst, Floris and  Garc{\'i}a-V{\'a}zquez, Ver{\'o}nica},
     title = {Catheter pose-dependent virtual angioscopy images visualized on augmented reality glasses},
   journal = {Current Directions in Biomedical Engineering},
    volume = {5},
    number = {1},
      year = {2019},
     keywords = {NavEVAR},
     pages = {289-291},
     url={https://www.degruyter.com/view/j/cdbme.2019.5.issue-1/cdbme-2019-0073/cdbme-2019-0073.xml}
}

@INPROCEEDINGS{kraft2019,
     author = {Kraft, Valentin and Strehlow, Jan and J{\"{a}}ckle, Sonja and Garc{\'i}a-V{\'a}zquez, Ver{\'o}nica and Link, Florian and von Haxthausen, Felix and Schenk, Andrea and Schumann, Christian},
      month = sep,
      title = {A comparison of streaming methods for the Microsoft HoloLens},
  booktitle = {Tagungsgband der 18. Jahrestagung der Deutschen Gesellschaft f{\"u}r Computer- und Roboterassistierte Chirurgie (CURAC)},
       year = {2019},
      pages = {212-216},
  publisher = {Oliver Burgert, Hochschule Reutlingen, Bernhard Hirt, Universit{\"a}t T{\"u}bingen},
   location = {Reutlingen (Germany)},
       isbn = {978-3-00-063717-9}
}

@incollection{jaeckle2019shape,
  title={Shape Sensing with Fiber Bragg Grating Sensors},
  author={J{\"a}ckle, Sonja and Strehlow, Jan and Heldmann, Stefan},
  booktitle={Bildverarbeitung f{\"u}r die Medizin 2019},
  pages={258--263},
  year={2019},
  publisher={Springer},
  keywords = {NavEVAR},
  url={https://link.springer.com/chapter/10.1007%2F978-3-658-25326-4_58},
}

@Book{LellmannBurgerModersitzki2019,
  title =     {Proceedings of the 7th International Conference On Scale Space and Variational Methods in Computer Vision (SSVM 2019)},
  publisher = {Springer},
  year =      {2019},
  author = {Lellmann, J. and Burger, M. and Modersitzki, J. (eds.)},
  series =    {Lecture Notes in Computer Science}
}

@InProceedings{BudelmannPapenbergLellmann2018,
  author =    {Budelmann, Daniel and K{\"o}nig, Lars and Papenberg, Nils and Lellmann, Jan},
  title =     {Fully-Deformable 3D Image Registration in Two Seconds},
  booktitle = {Bildverarbeitung f{\"u}r die Medizin 2019},
  year =      {2019},
  editor =    {Handels, Heinz and Deserno, Thomas M. and Maier, Andreas and Maier-Hein, Klaus Hermann and Palm, Christoph and Tolxdorff, Thomas},
  pages =     {302--307},
  address =   {Wiesbaden},
  publisher = {Springer Fachmedien Wiesbaden}
}

@article{OliverEtAl2019,
author = {Klein, Oliver and Kanter, Frederic and Kulbe, Hagen and Jank, Paul and Denkert, Carsten and Nebrich, Grit and Schmitt, Wolfgang D. and Wu, Zhiyang and Kunze, Catarina A. and Sehouli, Jalid and Darb-Esfahani, Silvia and Braicu, Ioana and Lellmann, Jan and Thiele, Herbert and Taube, Eliane T.},
title = {MALDI-Imaging for Classification of Epithelial Ovarian Cancer Histotypes from a Tissue Microarray Using Machine Learning Methods},
journal = {PROTEOMICS – Clinical Applications},
volume = {13},
number = {1},
pages = {1700181},
doi = {10.1002/prca.201700181},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/prca.201700181},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/prca.201700181},
abstract = {Purpose Precise histological classification of epithelial ovarian cancer (EOC) has immanent diagnostic and therapeutic consequences, but remains challenging in histological routine. The aim of this pilot study is to examine the potential of matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry in combination with machine learning methods to classify EOC histological subtypes from tissue microarray. Experimental design Formalin-fixed-paraffin-embedded tissue of 20 patients with ovarian clear-cell, 14 low-grade serous, 19 high-grade serous ovarian carcinomas, and 14 serous borderline tumors are analyzed using MALDI-Imaging. Classifications are computed by linear discriminant analysis (LDA), support vector machines with linear (SVM-lin) and radial basis function kernels (SVM-rbf), a neural network (NN), and a convolutional neural network (CNN). Results MALDI-Imaging and machine learning methods result in classification of EOC histotypes with mean accuracy of 80\% for LDA, 80\% SVM-lin, 74\% SVM-rbf, 83\% NN, and 85\% CNN. Based on sensitivity (69–100\%) and specificity (90–99\%), CCN and NN are most suited to EOC classification. Conclusion and clinical relevance The pilot study demonstrates the potential of MALDI-Imaging derived proteomic classifiers in combination with machine learning algorithms to discriminate EOC histotypes. Applications may support the development of new prognostic parameters in the assessment of EOC.},
year = {2019}
}

@article{hering2019memory,
  title={Memory-efficient 2.5 D convolutional transformer networks for multi-modal deformable registration with weak label supervision applied to whole-heart CT and MRI scans},
  author={Hering, Alessa and Kuckertz, Sven and Heldmann, Stefan and Heinrich, Mattias P},
  journal={International journal of computer assisted radiology and surgery},
  volume={14},
  number={11},
  pages={1901--1912},
  year={2019},
  publisher={Springer}
}

@incollection{hering2019BVM,
  title={Enhancing label-driven deep deformable image registration with local distance metrics for state-of-the-art cardiac motion tracking},
  author={Hering, Alessa and Kuckertz, Sven and Heldmann, Stefan and Heinrich, Mattias P},
  booktitle={Bildverarbeitung f{\"u}r die Medizin 2019},
  pages={309--314},
  year={2019},
  publisher={Springer},
  url={http://dx.doi.org/10.1007%2F978-3-658-25326-4_69},
}

@inproceedings{hering2019SPIE,
author = {Hering, Alessa and Heldmann, Stefan},
title = {{Unsupervised learning for large motion thoracic CT follow-up registration}},
volume = {10949},
booktitle = {Medical Imaging 2019: Image Processing},
organization = {International Society for Optics and Photonics},
publisher = {SPIE},
pages = {1-7},
year = {2019},
doi = {10.1117/12.2506962},
URL = {https://doi.org/10.1117/12.2506962}
}

@inproceedings{hering2019MIDL,
author = {Meine, Hans and Hering, Alessa},
title = {{Efficient Prealignment of CT Scans for Registration through a Bodypart Regressor}},
volume = {102},
booktitle = {Proceedings of Medical Imaging with Deep Learning (MIDL 2019)},
pages = {1-4},
year = {2019},
}

@inproceedings{hering2019MICCAI,
author = {Hering, Alessa and van Ginneken, Bram and Heldmann, Stefan},
title = {{mlVIRNET: Multilevel Variational Image Registration Network}},
volume = {11769},
booktitle = {Proceeding of Medical Image Computing and Computer Assisted Intervention (MICCAI 2019)},
publisher = {Springer},
pages = {257-265},
year = {2019},
doi = {10.1007/978-3-030-32226-7_29},
URL = {https://doi.org/10.1007/978-3-030-32226-7_29}
}

@article{Lotz2019,
  author={Bulten, Wouter and Bándi, Péter and Hoven, Jeffrey and van de Loo, Rob and Lotz, Johannes and Weiss, Nick and van der Laak, Jeroen and van Ginneken, Bram and Hulsbergen-van de Kaa, Christina and Litjens, Geert },
  title={Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard},
  journal={Scientific Reports},
  year={2019},
  volume={9},
  article={864},
  url={https://doi.org/10.1038/s41598-018-37257-4},
}

@article{meine2019efficient,
  title={Efficient Prealignment of CT Scans for Registration through a Bodypart Regressor},
  author={Meine, Hans and Hering, Alessa},
  journal={arXiv preprint arXiv:1909.08898},
  year={2019}
}

@incollection{CHEN2019579,
title = {Chapter 15 - Image and surface registration},
editor = {Ron Kimmel and Xue-Cheng Tai},
series = {Handbook of Numerical Analysis},
publisher = {Elsevier},
volume = {20},
pages = {579-611},
year = {2019},
booktitle = {Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 2},
issn = {1570-8659},
doi = {https://doi.org/10.1016/bs.hna.2019.07.001},
url = {https://www.sciencedirect.com/science/article/pii/S1570865919300146},
author = {Ke Chen and Lok Ming Lui and Jan Modersitzki},
keywords = {Image registration, Surface registration, Variational models, 35A15, 37E30, 49J40, 49Q05, 62H35, 62M40, 65D18, 80M30}

@article{grob2019accuracy,
  title={Accuracy of registration algorithms in subtraction CT of the lungs: A digital phantom study},
  author={Grob, Dagmar and Oostveen, Luuk and R{\"u}haak, Jan and Heldmann, Stefan and Mohr, Brian and Michielsen, Koen and Dorn, Sabrina and Prokop, Mathias and Kachelrie$\beta$, Marc and Brink, Monique and others},
  journal={Medical physics},
  volume={46},
  number={5},
  pages={2264--2274},
  year={2019},
  publisher={Wiley Online Library}
}

@article{hager2019maschinelles,
  title={Maschinelles Lernen f{\"u}r Momentum-basierte Bildgebung},
  author={H{\"a}ger, Stephanie},
  year={2019}
}

@article{lotz2019robust,
  title={Robust, fast and accurate: a 3-step method for automatic histological image registration},
  author={Lotz, Johannes and Weiss, Nick and Heldmann, Stefan},
  journal={arXiv preprint arXiv:1903.12063},
  year={2019}
}

@inproceedings{brehmer2018novel,
  title={A Novel Similarity Measure for Image Sequences},
  author={Brehmer, Kai and Wacker, Benjamin and Modersitzki, Jan},
  booktitle={International Workshop on Biomedical Image Registration},
  pages={47--56},
  year={2018},
  organization={Springer},
  url={{{https://arxiv.org/abs/1907.09741}}},
  doi={{{10.1007/978-3-319-92258-4_5}}}
}

@phdthesis{2018-PhD-Konig,
  Author = {Lars König},
  Title = {Matrix-free approaches for deformable image registration with large-scale and real-time applications in medical imaging},
  School = {Institute of Mathematics and Image Computing, University of L\"ubeck},
  Year = {2018},
}

@article{garcia2018navigation,
  title={Navigation and visualisation with HoloLens in endovascular aortic repair},
  author={Garc{\'i}a-V{\'a}zquez, Ver{\'o}nica and von Haxthausen, Felix and J{\"a}ckle, Sonja and Schumann, Christian and Kuhlemann, Ivo and Bouchagiar, Juljan and H{\"o}fer, Anna-Catharina and Matysiak, Florian and H{\"u}ttmann, Gereon and Goltz, Jan Peter and others},
  journal={Innovative Surgical Sciences},
  volume={3},
  number={3},
  pages={167--177},
  year={2018},
  publisher={De Gruyter},
  keywords={NavEVAR},
  url={https://degruyter.com/downloadpdf/j/iss.2018.3.issue-3/iss-2018-2001/iss-2018-2001.pdf}
}

@incollection{jaeckle2018rigid,
  title={Rigid Lens--Locally Rigid Approximations of Deformable Registration for Change Assessment in Thorax-Abdomen CT Follow-Up Scans},
  author={J{\"a}ckle, Sonja and Heldmann, Stefan},
  booktitle={Image Analysis for Moving Organ, Breast, and Thoracic Images},
  pages={272--283},
  year={2018},
  publisher={Springer},
  url={https://link.springer.com/chapter/10.1007/978-3-030-00946-5_27},
}

@article{loewenhauser2018functional,
  title={Functional Lifting for Variational Problems with Higher-Order},
  author={Loewenhauser, Benedikt and Lellmann, Jan},
  journal={Imaging, Vision and Learning Based on Optimization and PDEs: IVLOPDE, Bergen, Norway, August 29--September 2, 2016},
  pages={101},
  year={2018},
  publisher={Springer},
  URL={https://link.springer.com/chapter/10.1007%2F978-3-319-91274-5_5}
}

@article{hanson2018estimating,
  title={Estimating the discretization dependent accuracy of perfusion in coupled capillary flow measurements},
  author={Hanson, Erik A and Sandmann, Constantin and Malyshev, Alexander and Lundervold, Arvid and Modersitzki, Jan and Hodneland, Erlend},
  journal={PloS one},
  volume={13},
  number={7},
  pages={e0200521},
  year={2018},
  publisher={Public Library of Science}
}

@article{mader2018detection,
  title={Detection and localization of spatially correlated point landmarks in medical images using an automatically learned conditional random field},
  author={Mader, Alexander Oliver and Lorenz, Cristian and Bergtholdt, Martin and von Berg, Jens and Schramm, Hauke and Modersitzki, Jan and Meyer, Carsten},
  journal={Computer Vision and Image Understanding},
  volume={176},
  pages={45--53},
  year={2018},
  publisher={Elsevier}
}

@inproceedings{brehmer2018simultaneous,
  title={Simultaneous Registration of Image Sequences – a novel singular value
based images similarity measure},
  author={Brehmer, Kai and Wacker, Benjamin and Modersitzki, Jan},
  booktitle={Proceedings in Applied Mathematics and Mechanics - 89th GAMM Annual Meeting},
  pages={},
  year={2018},
  organization={Wiley}
}

@article{korolev2018image,
  title={Image reconstruction with imperfect forward models and applications in deblurring},
  author={Korolev, Yury and Lellmann, Jan},
  journal={SIAM Journal on Imaging Sciences},
  volume={11},
  number={1},
  pages={197--218},
  year={2018},
  publisher={SIAM}
}

@inproceedings{gregori2018feasibility,
  title={Feasibility of fully automated atrophy measurement of the upper cervical spinal cord for group analyses and patientindividual diagnosis support in MS},
  author={Gregori, J and Cornelissen, C and Hoffmann, S and Treiber, M and Randoll, S and Heldmann, S and Klein, J and Opfer, R and Spies, L and Gass, A and others},
  booktitle={MULTIPLE SCLEROSIS JOURNAL},
  volume={24},
  pages={623--624},
  year={2018},
  organization={SAGE PUBLICATIONS LTD 1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND}
}

@inproceedings{jackle2018visuelle,
  title={Visuelle Unterst{\"u}tzung bei endovaskul{\"a}ren Eingriffen durch Darstellung einer virtuellen Angioskopie auf der HoloLens},
  author={J{\"a}ckle, Sonja and von Haxthausen, Felix and Garc{\'\i}a-V{\'a}zquez, Ver{\'o}nica and Schumann, Christian and Kleemann, Markus and Ernst, Floris and Papenberg, Nils},
  booktitle={34. Jahrestagung der Deutschen Gesellschaft f{\"u}r Gef{\"a}{\ss}chirurgie und Gef{\"a}{\ss}medizin (DGG)},
  year={2018}
}

@phdthesis{lange2018mehrgitterverfahren,
  title={Mehrgitterverfahren zur FEM-basierten elastischen Registrierung histologischer Serienschnitte},
  author={Lange, A},
  year={2018}
}

@article{hofener2018deep,
  title={Deep learning nuclei detection: A simple approach can deliver state-of-the-art results},
  author={H{\"o}fener, Henning and Homeyer, Andr{\'e} and Weiss, Nick and Molin, Jesper and Lundstr{\"o}m, Claes F and Hahn, Horst K},
  journal={Computerized Medical Imaging and Graphics},
  volume={70},
  pages={43--52},
  year={2018},
  publisher={Elsevier}
}

@article{schwen2018data,
  title={Data-driven discovery of immune contexture biomarkers},
  author={Schwen, Lars Ole and Andersson, Emilia and Korski, Konstanty and Weiss, Nick and Haase, Sabrina and Gaire, Fabien and Hahn, Horst K and Homeyer, Andr{\'e} and Grimm, Oliver},
  journal={Frontiers in oncology},
  volume={8},
  pages={412055},
  year={2018},
  publisher={Frontiers}
}

@article{konig2018matrix,
author = {König, Lars and Rühaak, Jan and Derksen, Alexander and Lellmann, Jan},
journal = {SIAM Journal on Scientific Computing},
title = {A matrix-free approach to parallel and memory-efficient deformable image registration},
year = {2018},
volume = {40},
number = {3},
pages = {B858--B888},
url = {https://arxiv.org/abs/1804.10541},
doi = {10.1137/17M1125522}
}

@inproceedings{weiss2018towards,
  title={Towards interactive breast tumor classification using transfer learning},
  author={Weiss, Nick and Kost, Henning and Homeyer, Andr{\'e}},
  booktitle={International conference image analysis and recognition},
  pages={727--736},
  year={2018},
  organization={Springer}
}

@article{VogtLellmann2018,
author ={Vogt, T. and Lellmann, J.},
publisher={Springer International Publishing},
title={Measure-Valued Variational Models with Applications to Diffusion-Weighted Imaging},
journal={Journal of Mathematical Imaging and Vision},
year={2018},
month={Jun},
day={08},
issn={1573-7683},
doi={10.1007/s10851-018-0827-8},
url={https://arxiv.org/pdf/1710.00798.pdf}
}

@phdthesis{2018-PhD-Polzin,
  Author = {Thomas Polzin},
  Title = {Large Deformation Diffeomorphic Metric Mappings -- Theory, Numerics, and Applications},
  School = {Institute of Mathematics and Image Computing, University of L\"ubeck},
  Year = {2018},
}

@article{rust3robust,
  title={A robust algorithm for optic disc segmentation and fovea detection in retinal fundus images},
  author={Rust, Caterina and H{\"a}ger, Stephanie and Traulsen, Nadine and Modersitzki, Jan},
  journal={Current Directions in Biomedical Engineering},
  volume={3},
  number={2},
  year={2017},
  pages={533--537},
  publisher={De Gruyter}
}

@article{ruthotto2017stabilized,
  title={A stabilized multigrid solver for hyperelastic image registration},
  author={Ruthotto, Lars and Greif, Chen and Modersitzki, Jan},
  journal={Numerical Linear Algebra with Applications},
  volume={24},
  number={5},
  pages={e2095},
  year={2017},
  publisher={Wiley Online Library}
}

@incollection{mader2017detection,
  title={Detection and Localization of Landmarks in the Lower Extremities Using an Automatically Learned Conditional Random Field},
  author={Mader, Alexander Oliver and Lorenz, Cristian and Bergtholdt, Martin and von Berg, Jens and Schramm, Hauke and Modersitzki, Jan and Meyer, Carsten},
  booktitle={Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics},
  pages={64--75},
  year={2017},
  publisher={Springer}
}

@inproceedings{weiler2017fully,
  title={Fully automated detection, segmentation and quantification of mean cross-sectional area of the spinal cord},
  author={Weiler, F and Hallmann, MF and Schwier, M and Hildebrandt, H and Gregori, J and Spiess, L and Klein, J and Heldmann, S},
  booktitle={MULTIPLE SCLEROSIS JOURNAL},
  volume={23},
  pages={149--150},
  year={2017},
  organization={SAGE PUBLICATIONS LTD 1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND}
}

@inproceedings{horn2017endovascular,
  title={Endovascular interventions proceeded under contrast agent and radiation sparing using navigation and imaging techniques for holographic visualisation},
  author={Horn, Marco and Goltz, Jan Peter and Stahlberg, Erik and Papenberg, Nils and Ernst, Floris and Kleemann, Markus},
  booktitle={European Symposium on Vascular Biomaterials, Strasbourg},
  year={2017}
}

@ARTICLE{ruhaak2017matrix,
  author = {R\"{u}haak, Jan and K\"{o}nig, Lars and Tramnitzke, Florian and K\"{o}stler, Harald and Modersitzki, Jan},
  title = {A {M}atrix-{F}ree {A}pproach to {E}fficient {A}ffine-{L}inear {I}mage {R}egistration on {CPU} and {GPU}},
  journal = {{J}ournal of {R}eal-{T}ime {I}mage {P}rocessing},
  year      = {2017},
  volume    = {13},
  number    = {1},
  pages     = {205--225},
  issn      = {1861-8219},
  publisher = {Springer},
  url = {http://dx.doi.org/10.1007/s11554-016-0564-4}
}

@article{ruhaak2017estimation,
  title={Estimation of Large Motion in Lung CT by Integrating Regularized Keypoint Correspondences into Dense Deformable Registration},
  author={R{\"u}haak, Jan and Polzin, Thomas and Heldmann, Stefan and Simpson, Ivor J. A. and Handels, Heinz and Modersitzki, Jan and Heinrich, Mattias P.},
  journal={IEEE Transactions on Medical Imaging},
  volume = {36},
  number = {8},
  pages = {1746--1757},
  year={2017},
  publisher={IEEE}
}

@phdthesis{2017-PhD-Sandmann,
  Author = {Constantin M. Sandmann},
  Title = {Dynamic Models and Coupling in Medical 4D Imaging},
  School = {Institute of Mathematics and Image Computing, University of L\"ubeck},
  Year = {2017},
}

@INPROCEEDINGS{vogt2017qball,
author={Vogt, Thomas and Lellmann, Jan},
title={An Optimal Transport-Based Restoration Method for Q-Ball Imaging},
booktitle={Scale Space and Variational Methods in Computer Vision: 6th International Conference, SSVM 2017, Kolding, Denmark, June 4-8, 2017, Proceedings},
pages={271--282},
year={2017},
publisher={Springer International Publishing},
editor={Lauze, Fran{\c{c}}ois and Dong, Yiqiu and Dahl, Anders Bjorholm},
doi={{{10.1007/978-3-319-58771-4_22}}}
}

@article{homeyer2017automated,
  title={Automated quantification of steatosis: agreement with stereological point counting},
  author={Homeyer, Andr{\'e} and Nasr, Patrik and Engel, Christiane and Kechagias, Stergios and Lundberg, Peter and Ekstedt, Mattias and Kost, Henning and Weiss, Nick and Palmer, Tim and Hahn, Horst Karl and others},
  journal={Diagnostic pathology},
  volume={12},
  number={1},
  pages={80},
  year={2017},
  publisher={Springer}
}

@article{SandmannEtAl2016,
author = {Constantin Sandmann and Erlend Hodneland and Jan Modersitzki},
title = {A practical guideline for T1 reconstruction from various flip angles in MRI},
journal = {Journal of Algorithms \& Computational Technology},
volume = {10},
number = {4},
pages = {213-223},
year = {2016},
URL = {http://dx.doi.org/10.1177/1748301816656288},
abstract = { A fast and robust method for T1 estimation in MRI is the so-called variable flip angle technique. We introduce a novel family of T1 reconstruction methods from data acquired with various flip angles and propose a family member which combines the robustness of a nonlinear- with the computational advantages of a linear reconstruction. The constructed family contains the most common approaches for T1 estimation, namely a linear and a nonlinear approach. A general sensitivity analysis for arbitrary members of the family is established. Advantages of the optimized reconstruction are demonstrated on phantom- as well as real data, showing improvements of up to 24\% as compared with the linear method. As a further means to stabilize T1 estimation, spatial stabilization methods are compared. We demonstrate on phantom and on real data that improved results can be obtained if not only T1 but also a second unknown M0 in the reconstruction is stabilized. }
}

@INPROCEEDINGS{PolzinEtAl2016,
  author = {Polzin, Thomas and Niethammer, Marc and Heinrich, Mattias Paul and
	Handels, Heinz and Modersitzki, Jan},
  title = {{Memory Efficient LDDMM for Lung CT}},
  booktitle = {Medical Image Computing and Computer-Assisted Intervention 2016},
  pages = {28--36},
  year = {2016},
  publisher = {Springer},
 editor = {Sebastién Ourselin and Leo Joskowicz and Mert R. Sabuncu and Gozde Unal and William Wells}
}

@article{konig2016deformable,
  title={Deformable image registration for adaptive radiotherapy with guaranteed local rigidity constraints},
  author={K{\"o}nig, Lars and Derksen, Alexander and Papenberg, Nils and Haas, Benjamin},
  journal={Radiation Oncology},
  volume={11},
  number={1},
  pages={122},
  year={2016},
  publisher={BioMed Central},
doi={10.1186/s13014-016-0697-4}
}

@article{stutzer2016evaluation,
  title={Evaluation of a deformable registration algorithm for subsequent lung computed tomography imaging during radiochemotherapy},
  author={St{\"u}tzer, Kristin and Haase, Robert and Lohaus, Fabian and Barczyk, Steffen and Exner, Florian and L{\"o}ck, Steffen and R{\"u}haak, Jan and Lassen-Schmidt, Bianca and Corr, D{\"o}rte and Richter, Christian},
  journal={Medical Physics},
  volume={43},
  number={9},
  pages={5028--5039},
  year={2016},
  publisher={Wiley Online Library}
}

@InProceedings{Laude2016,
  author = {Laude, E. and M{\"o}llenhoff, T. and M{\"o}ller, M. and Lellmann, J and Cremers, D.},
  title =  {Sublabel-Accurate Convex Relaxation of Vectorial Multilabel Energies},
  year =   {2016},
  booktitle  = {Proc. Europ. Conf. Comp. Vision}
}