@article{schafer2024overcoming,
  title={Overcoming data scarcity in biomedical imaging with a foundational multi-task model},
  author={Schäfer, Raphael and Nicke, Till and Höfener, Henning and Lange, Annkristin and Merhof, Dorit and Feuerhake, Friedrich and Schulz, Volkmar and Lotz, Johannes and Kiessling, Fabian},
  journal={Nature Computational Science},
  volume={4},
  number={7},
  pages={495--509},
  year={2024},
  publisher={Nature Publishing Group US New York}
}

@misc{nicke2024tissueconceptssupervisedfoundation,
      title={Tissue Concepts: supervised foundation models in computational pathology}, 
      author={Till Nicke and Jan Raphael Schaefer and Henning Hoefener and Friedrich Feuerhake and Dorit Merhof and Fabian Kiessling and Johannes Lotz},
      year={2024},
      eprint={2409.03519},
      archivePrefix={arXiv},
      primaryClass={eess.IV},
      url={https://arxiv.org/abs/2409.03519}, 
}

@phdthesis{meli2024quantum,
  title={Quantum Algorithms for Binary Problems with Applications to Image Processing},
  author={Meli, Natacha Kuete},
  year={2024},
  school={Universität zu Lübeck} 
}

@InProceedings{bednarski2023emnef,
  author    = {Bednarski, Danielle and Lellmann, Jan},
  title     = {EmNeF: Neural Fields for Embedded Variational Problems in Imaging},
  booktitle = {Scale Space and Variational Methods in Computer Vision},
  year      = {2023},
  editor    = {Calatroni, Luca and Donatelli, Marco and Morigi, Serena and Prato, Marco and Santacesaria, Matteo},
  pages     = {137--148},
  address   = {Cham},
  publisher = {Springer International Publishing},
  doi       = {https://doi.org/10.1007/978-3-031-31975-4_11},
  isbn      = {978-3-031-31975-4},
 url = {https://link.springer.com/chapter/10.1007/978-3-031-31975-4_11},
}

@article{alpers2023evaluation,
  title={Evaluation of the EsteR Toolkit for COVID-19 Decision Support: Sensitivity Analysis and Usability Study},
  author={Alpers, Rieke and K{\"u}hne, Lisa and Truong, Hong-Phuc and Zeeb, Hajo and Westphal, Max and J{\"a}ckle, Sonja},
  journal={JMIR Formative Research},
  volume={7},
  pages={e44549},
  year={2023},
  publisher={JMIR Publications Toronto, Canada}
}

@phdthesis{2023-PhD-Kanter,
  Author = {{Frederic Georg Kanter}},
  Title = {Deep Learning for Mass Spectrometry Imaging and Image Registration},
  School = {Institute of Mathematics and Image Computing, University of L\"ubeck},
  Year = {2023},
}

@article{kanter2023classification,
  title={Classification of Pancreatic Ductal Adenocarcinoma Using MALDI Mass Spectrometry Imaging Combined with Neural Networks},
  author={Kanter, Frederic and Lellmann, Jan and Thiele, Herbert and Kalloger, Steve and Schaeffer, David F and Wellmann, Axel and Klein, Oliver},
  journal={Cancers},
  volume={15},
  number={3},
  pages={686},
  year={2023},
  publisher={MDPI}
}

@article{kuete2023universal,
  title={A universal quantum algorithm for weighted maximum cut and Ising problems},
  author={Kuete Meli, Natacha and Mannel, Florian and Lellmann, Jan},
  journal={Quantum Information Processing},
  volume={22},
  number={7},
  pages={279},
  year={2023},
  publisher={Springer}
}

@InProceedings{pmlr-v172-kanter22a,
title = {A Flexible Meta Learning Model for Image Registration},
author = {Kanter, Frederic and Lellmann, Jan},
booktitle = {Proceedings of The 5th International Conference on Medical Imaging with Deep Learning},
pages = {638-652},
year = {2022},
editor = {Konukoglu, Ender and Menze, Bjoern and Venkataraman, Archana and Baumgartner, Christian and Dou, Qi and Albarqouni, Shadi},  
volume =  {172},  
series =  {Proceedings of Machine Learning Research},  
month =  {06--08 Jul},  
publisher = {PMLR}
}

@incollection{jackle2022ester,
  title={EsteR--A Digital Toolkit for COVID-19 Decision Support in Local Health Authorities},
  author={J{\"a}ckle, Sonja and Alpers, Rieke and K{\"u}hne, Lisa and Schumacher, Jakob and Geisler, Benjamin and Westphal, Max},
  booktitle={German Medical Data Sciences 2022--Future Medicine: More Precise, More Integrative, More Sustainable!},
  pages={17--24},
  year={2022},
  publisher={IOS Press}
}

@inproceedings{hering2022towards,
  title={Towards more efficient tumor follow-up assessment using AI assistance},
  author={Hering, Alessa and Peisen, Felix and Moltz, Jan Hendrik},
  booktitle={Medical Imaging with Deep Learning},
  year={2022}
}

@Article{Mannel5,
title={{SHINE}: {SH}aring the {IN}verse Estimate from the forward pass for bi-level optimization and implicit models},
author={Ramzi, Zaccharie and Mannel, Florian and Bai, Shaojie and Starck, Jean-Luc and Ciuciu, Philippe and Moreau, Thomas},
FJournal={The Tenth International Conference on Learning Representations (ICLR)},
year={2022},
Language={English},
url={https://openreview.net/forum?id=-ApAkox5mp}
}

@incollection{hager2022robin,
  title={Robust Intensity-based Initialization for 2D-3D Pelvis Registration
(RobIn)},
  author={Häger, Stephanie and Lange, Annkristin and Heldmann, Stefan {and} Modersitzki, Jan and Petersik, Andreas and Schröder, Manuel and Gottschling, Heiko and Lieth, Thomas and Zähringer, Erich and Moltz, Jan H},
  booktitle={Bildverarbeitung für die Medizin 2022},
  pages={69--74},
  year={2022},
  publisher={Springer}
}

@article{Miesen_2022, 
doi={10.1242/dmm.046342}, 
url={https://doi.org/10.1242%2Fdmm.046342}, 
year={2022}, 
month={mar}, 
publisher={The Company of Biologists}, 
volume={15}, 
number={3}, 
author={Miesen, Laura and Bándi, Péter and Willemsen, Brigith and Mooren, Fieke and Strieder, Thiago and Boldrini, Eva  and Drenic, Vedran and Eymael, Jennifer and Wetzels, Roy and Lotz, Johannes and Weiss, Nick and  Steenbergen, Eric and van Kuppevelt, Toin H. and van Erp, Merijn and van der Laak, Jeroen and Endlich, Nicole and Moeller, Marcus J. and Wetzels, Jack F. M. and Jansen, Jitske and Smeets, Bart}, 
title={Parietal epithelial cells maintain the epithelial cell continuum forming Bowman's space in focal segmental glomerulosclerosis}, 
journal={Disease Models & Mechanisms}
}

@Article{Mannel2,
Author={{Mannel, Florian}},
Title={{On the convergence of Broyden’s method and some accelerated schemes for singular problems}},
FJournal={{IMA Journal of Numerical Analysis}},
Volume={},
Number={},
Pages={1--29},
Year={2022},
Language={English},
DOI= 10.1093/imanum/drab096},
eprint={https://academic.oup.com/imajna/advance-article-pdf/doi/10.1093/imanum/drab096/42198372/drab096.pdf},
}

@Article{bednarski2022inverse,
  author  = {Danielle Bednarski and Jan Lellmann},
  title   = {Inverse Scale Space Iterations for Non-Convex Variational Problems: The Continuous and Discrete Case},
  journal = {J Math Imaging Vis},
  year    = {2022},
  doi     = {10.1007/s10851-022-01125-8},
  url = {https://link.springer.com/article/10.1007/s10851-022-01125-8},
}

@article{peisen2022combination,
  title={Combination of Whole-Body Baseline CT Radiomics and Clinical Parameters to Predict Response and Survival in a Stage-IV Melanoma Cohort Undergoing Immunotherapy},
  author={Peisen, Felix and H{\"a}nsch, Annika and Hering, Alessa and Brendlin, Andreas S and Afat, Saif and Nikolaou, Konstantin and Gatidis, Sergios and Eigentler, Thomas and Amaral, Teresa and Moltz, Jan H and others},
  journal={Cancers},
  volume={14},
  number={12},
  pages={2992},
  year={2022},
  publisher={Multidisciplinary Digital Publishing Institute}
}

@article{haase2022deformable,
  title={Deformable groupwise image registration using low-rank and sparse decomposition},
  author={Haase, Roland and Heldmann, Stefan and Lellmann, Jan},
  journal={Journal of Mathematical Imaging and Vision},
  volume={64},
  number={2},
  pages={194--211},
  year={2022},
  publisher={Springer}
}

@phdthesis{hering2022deep,
  title={Deep-Learning-based Image Registration and Tumor Follow-Up Analysis},
  author={Hering, AD},
  year={2022},
  school={[Sl]:[Sn]}
}

@article{hansen2022continuous,
  title={Continuous benchmarking in medical image registration-review of the current state of the Learn2Reg challenge},
  author={Hansen, Lasse and Hering, Alessa and Großbröhmer, Christoph and Heinrich, Mattias P},
  journal={Medical Imaging with Deep Learning},
  year={2022}
}

@article{Budelmann2022100001,
title={Automated Detection of Portal Fields and Central Veins in
Whole-Slide Images of Liver Tissue},
journal={Journal of Pathology Informatics},
volume={13},
pages={100001},
year={2022},
issn={2153-3539},
doi={https://doi.org/10.1016/j.jpi.2022.100001},
url={https://www.sciencedirect.com/science/article/pii/S2153353922000013},
author={Budelmann, Daniel and Laue, Hendrick and Weiss, Nick and Dahmen, Uta and D’Alessandro, Lorenza A. and Biermayer , Ina and Klingmüller, Ursula and Ghallab, Ahmed and Hassan, Reham and Begher-Tibbe, Brigitte and Hengstler, Jan G. and Schwen, Lars Ole},
keywords={liver, portal field, central vein, object detection,
convolutional neural network, zonated quantification}
}

@inproceedings{Meli2022,
  title={An Iterative Quantum Approach for Transformation Estimation From Point Sets},
  author={Kuete Meli, N. and Mannel, F. and Lellmann, J.},
  booktitle={Computer Vision and Pattern Recognition},
  pages={529--537},
  year={2022}
}

@Article{Mannel1,
Author={Hafemeyer, Dominik and Mannel, Florian},
Title={A path-following inexact Newton method for {PDE}-constrained optimal control in {BV}},
FJournal={{Computational Optimization and Applications}},
Journal={{COAP}},
Volume={82},
Number={3},
Pages={753--794},
Year={2022},
Language={English},
doi = {10.1007/s10589-022-00370-2},
}

@Article{Mannel3,
Author={{Mannel, Florian and Rund, Armin}},
Title={{A hybrid semismooth quasi-Newton method for structured nonsmooth operator equations in Banach spaces}},
FJournal={{Journal of Convex Analysis}},
Journal={{JoCA}},
Volume={29},
Number={1},
Pages={183--204},
Year={2022},
Language={English},
url={https://www.heldermann.de/JCA/JCA29/JCA291/jca29011.htm},
}

@incollection{jackle20223d,
  title={3D Stent Graft Guidance Based on Tracking Systems},
  author={J{\"a}ckle, Sonja and Eixmann, Tim and Matysiak, Florian and Sieren, Malte M and Horn, Marco and Schulz-Hildebrandt, Hinnerk and H{\"u}ttmann, Gereon and P{\"a}tz, Torben},
  booktitle={Bildverarbeitung f{\"u}r die Medizin 2022},
  pages={253--253},
  year={2022},
  publisher={Springer}
}

@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.},
}

@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}
}

@phdthesis{2021-PhD-Brehmer,
  Author = {{Kai Brehmer}},
  Title = {SqN: A Novel Distance Measure for Multiple Images and Applications},
  School = {Institute of Mathematics and Image Computing, University of L\"ubeck},
  Year = {2021},
}

@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{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}
}

@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}
}

@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}
}

@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{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{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},
}

@incollection{jaeckle20213BVM_3DCatheter,
  title={Abstract: 3D Guidance Including Shape Sensing of a Stentgraft System},
  author={J{\"a}ckle, Sonja and Garc\'ia-V{\'a}zquez, Ver{\'o}nica and Eixmann, Tim and Matysiak, Florian and von Haxthausen, Felix and Sieren, Malte 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 2021},
  pages={34--34},
  year={2021},
  doi={10.1007/978-3-658-33198-6_9},
  url={https://link.springer.com/chapter/10.1007%2F978-3-658-33198-6_9},
  keywords={NavEVAR},
  publisher={Springer}
}

@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}
}

@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}
}

@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},
}

@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}
}

@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},
}

@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}
}

@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{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},
}

@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{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},
}

@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}
}

@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},
}

@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}}}
}

@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}
}

@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}
}

@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}
}

@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."
}

@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}
}

@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}
}

@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}
}

@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}
}

@inproceedings{hering2019mlvirnet,
  title={mlvirnet: Multilevel variational image registration network},
  author={Hering, Alessa and Ginneken, Bram van and Heldmann, Stefan},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={257--265},
  year={2019},
  organization={Springer}
}

@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}}}
}

@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},
}

@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}
}

@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{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{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}
}

@inproceedings{hering2019unsupervised,
  title={Unsupervised learning for large motion thoracic CT follow-up registration},
  author={Hering, Alessa and Heldmann, Stefan},
  booktitle={Medical Imaging 2019: Image Processing},
  volume={10949},
  pages={331--337},
  year={2019},
  organization={SPIE}
}

@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{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}
}

@Article{Klein2018,
  author =  {Klein, O. and Kanter, F. and Kulbe, H. and Jank, P. and Denkert, C. and Nebrich, G. and Schmitt, W.D. and Wu, Z. and Kunze, C.A. and Sehouli, J. and Darb-Eshfahani, S. and Braicu, I. and Lellmann, J. and Thiele, H. and Taube, E.T.},
  title =   {{MALDI}-Imaging for Classification of Epithelial Ovarian Cancer Histotypes from a Tissue Microarray Using Machine Learning Methods},
  journal = {Proteomics Clinical Applications},
  year =    {2019},
  volume =  {13},
  number =  {1},
  pages =   {1700181}
}

@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}
}

@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}
}

@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},
}

@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},
}

@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}
}

@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},
}

@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},
}

@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}
}

@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{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}}}
}

@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}
}

@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}
}

@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},
}

@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},
}