2024
Natacha Kuete Meli,
Quantum Algorithms for Binary Problems with Applications to Image Processing, Universität zu Lübeck, 2024.
Quantum Algorithms for Binary Problems with Applications to Image Processing, Universität zu Lübeck, 2024.
File: | Dateilink |
Bibtex: | @phdthesis{meli2024quantum, title={Quantum Algorithms for Binary Problems with Applications to Image Processing}, author={Meli, Natacha Kuete}, year={2024}, school={Universität zu Lübeck} } |
2023
Florian
Mannel,
Hari Om
Aggrawal, and
Jan
Modersitzki,
A structured L-BFGS method and its application to inverse problems, Inverse Problems , 2023.
A structured L-BFGS method and its application to inverse problems, Inverse Problems , 2023.
Natacha
Kuete Meli,
Florian
Mannel, and
Jan
Lellmann,
A universal quantum algorithm for weighted maximum cut and Ising problems, Quantum Information Processing , vol. 22, no. 7, pp. 279, 2023. Springer.
A universal quantum algorithm for weighted maximum cut and Ising problems, Quantum Information Processing , vol. 22, no. 7, pp. 279, 2023. Springer.
Frederic
Kanter,
Jan
Lellmann,
Herbert
Thiele,
Steve
Kalloger,
David F
Schaeffer,
Axel
Wellmann, and
Oliver
Klein,
Classification of Pancreatic Ductal Adenocarcinoma Using MALDI Mass Spectrometry Imaging Combined with Neural Networks, Cancers , vol. 15, no. 3, pp. 686, 2023. MDPI.
Classification of Pancreatic Ductal Adenocarcinoma Using MALDI Mass Spectrometry Imaging Combined with Neural Networks, Cancers , vol. 15, no. 3, pp. 686, 2023. MDPI.
Frederic Georg Kanter,
Deep Learning for Mass Spectrometry Imaging and Image Registration, Institute of Mathematics and Image Computing, University of Lübeck, 2023.
Deep Learning for Mass Spectrometry Imaging and Image Registration, Institute of Mathematics and Image Computing, University of Lübeck, 2023.
File: | kanter_small.pdf |
Bibtex: | @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}, } |
Danielle
Bednarski, and
Jan
Lellmann,
EmNeF: Neural Fields for Embedded Variational Problems in Imaging, in Scale Space and Variational Methods in Computer Vision , Calatroni, Luca and Donatelli, Marco and Morigi, Serena and Prato, Marco and Santacesaria, Matteo, Eds. Cham: Springer International Publishing, 2023. pp. 137--148.
EmNeF: Neural Fields for Embedded Variational Problems in Imaging, in Scale Space and Variational Methods in Computer Vision , Calatroni, Luca and Donatelli, Marco and Morigi, Serena and Prato, Marco and Santacesaria, Matteo, Eds. Cham: Springer International Publishing, 2023. pp. 137--148.
DOI: | https://doi.org/10.1007/978-3-031-31975-4_11 |
ISBN: | 978-3-031-31975-4 |
File: | 978-3-031-31975-4_11 |
Bibtex: | @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}, } |
Rieke
Alpers,
Lisa
Kühne,
Hong-Phuc
Truong,
Hajo
Zeeb,
Max
Westphal, and
Sonja
Jäckle,
Evaluation of the EsteR Toolkit for COVID-19 Decision Support: Sensitivity Analysis and Usability Study, JMIR Formative Research , vol. 7, pp. e44549, 2023. JMIR Publications Toronto, Canada.
Evaluation of the EsteR Toolkit for COVID-19 Decision Support: Sensitivity Analysis and Usability Study, JMIR Formative Research , vol. 7, pp. e44549, 2023. JMIR Publications Toronto, Canada.
2022
Frederic
Kanter, and
Jan
Lellmann,
A Flexible Meta Learning Model for Image Registration, in Proceedings of The 5th International Conference on Medical Imaging with Deep Learning , Konukoglu, Ender and Menze, Bjoern and Venkataraman, Archana and Baumgartner, Christian and Dou, Qi and Albarqouni, Shadi, Eds. PMLR, 06-.2022. pp. 638-652.
A Flexible Meta Learning Model for Image Registration, in Proceedings of The 5th International Conference on Medical Imaging with Deep Learning , Konukoglu, Ender and Menze, Bjoern and Venkataraman, Archana and Baumgartner, Christian and Dou, Qi and Albarqouni, Shadi, Eds. PMLR, 06-.2022. pp. 638-652.
Sonja
Jäckle,
Rieke
Alpers,
Lisa
Kühne,
Jakob
Schumacher,
Benjamin
Geisler, and
Max
Westphal,
EsteR -A Digital Toolkit for COVID-19 Decision Support in Local Health Authorities, in German Medical Data Sciences 2022--Future Medicine: More Precise, More Integrative, More Sustainable! , IOS Press, 2022, pp. 17--24.
EsteR -A Digital Toolkit for COVID-19 Decision Support in Local Health Authorities, in German Medical Data Sciences 2022--Future Medicine: More Precise, More Integrative, More Sustainable! , IOS Press, 2022, pp. 17--24.
Zaccharie
Ramzi,
Florian
Mannel,
Shaojie
Bai,
Jean-Luc
Starck,
Philippe
Ciuciu, and
Thomas
Moreau,
SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models, 2022.
SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models, 2022.
File: | forum |
Bibtex: | @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} } |
Stephanie
Häger,
Annkristin
Lange,
Jan
Heldmann,
Andreas
Petersik,
Manuel
Schröder,
Heiko
Gottschling,
Thomas
Lieth,
Erich
Zähringer, and
Jan H
Moltz,
Robust Intensity-based Initialization for 2D-3D Pelvis Registration (RobIn), in Bildverarbeitung für die Medizin 2022 , Springer, 2022, pp. 69--74.
Robust Intensity-based Initialization for 2D-3D Pelvis Registration (RobIn), in Bildverarbeitung für die Medizin 2022 , Springer, 2022, pp. 69--74.
Malte Maria
Sieren,
Sonja
Jäckle,
Tim
Eixmann,
Hinnerk
Schulz-Hildebrandt,
Florian
Matysiak,
Mark
Preuss,
Verónica
García-Vázquez,
Erik
Stahlberg,
Markus
Kleemann,
Jörg
Barkhausen, and
others,
Radiation-free Thoracic Endovascular Aneurysm Repair with Fiberoptic and Electromagnetic Guidance: A Phantom Study, Journal of Vascular and Interventional Radiology , 2022. Elsevier.
Radiation-free Thoracic Endovascular Aneurysm Repair with Fiberoptic and Electromagnetic Guidance: A Phantom Study, Journal of Vascular and Interventional Radiology , 2022. Elsevier.
Laura
Miesen,
Péter
Bándi,
Brigith
Willemsen,
Fieke
Mooren,
Thiago
Strieder,
Eva
Boldrini,
Vedran
Drenic,
Jennifer
Eymael,
Roy
Wetzels,
Johannes
Lotz,
Nick
Weiss,
Eric
Steenbergen,
Toin H.
Kuppevelt,
Merijn
Erp,
Jeroen
Laak,
Nicole
Endlich,
Marcus J.
Moeller,
Jack F. M.
Wetzels,
Jitske
Jansen, and
Bart
Smeets,
Parietal epithelial cells maintain the epithelial cell continuum forming Bowman's space in focal segmental glomerulosclerosis, Disease Models & Mechanisms , vol. 15, no. 3, 2022. The Company of Biologists.
Parietal epithelial cells maintain the epithelial cell continuum forming Bowman's space in focal segmental glomerulosclerosis, Disease Models & Mechanisms , vol. 15, no. 3, 2022. The Company of Biologists.
DOI: | 10.1242/dmm.046342 |
File: | 10.1242%2Fdmm.046342 |
Bibtex: | @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} } |
Florian Mannel,
On the convergence of Broyden’s method and some accelerated schemes for singular problems, pp. 1--29, 2022.
On the convergence of Broyden’s method and some accelerated schemes for singular problems, pp. 1--29, 2022.
DOI: | 10.1093/imanum/drab096 |
Bibtex: | @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}, } |
Danielle
Bednarski, and
Jan
Lellmann,
Inverse Scale Space Iterations for Non-Convex Variational Problems: The Continuous and Discrete Case, J Math Imaging Vis , 2022.
Inverse Scale Space Iterations for Non-Convex Variational Problems: The Continuous and Discrete Case, J Math Imaging Vis , 2022.
DOI: | 10.1007/s10851-022-01125-8 |
File: | s10851-022-01125-8 |
Bibtex: | @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}, } |
Alessa
Hering,
Felix
Peisen, and
Jan Hendrik
Moltz,
Towards more efficient tumor follow-up assessment using AI assistance, in Medical Imaging with Deep Learning , 2022.
Towards more efficient tumor follow-up assessment using AI assistance, in Medical Imaging with Deep Learning , 2022.
Roland
Haase,
Stefan
Heldmann, and
Jan
Lellmann,
Deformable groupwise image registration using low-rank and sparse decomposition, Journal of Mathematical Imaging and Vision , vol. 64, no. 2, pp. 194--211, 2022. Springer.
Deformable groupwise image registration using low-rank and sparse decomposition, Journal of Mathematical Imaging and Vision , vol. 64, no. 2, pp. 194--211, 2022. Springer.
AD Hering,
Deep-Learning-based Image Registration and Tumor Follow-up Analysis, 2022.
Deep-Learning-based Image Registration and Tumor Follow-up Analysis, 2022.
File: | Hering__Deep-Learning-based_Image_Registration_and_Tumor_Follow-up_Analysis-komprimiert.pdf |
Bibtex: | @phdthesis{hering2022deep, title={Deep-Learning-based Image Registration and Tumor Follow-Up Analysis}, author={Hering, AD}, year={2022}, school={[Sl]:[Sn]} } |
Lasse
Hansen,
Alessa
Hering,
Christoph
Großbröhmer, and
Mattias P
Heinrich,
Continuous benchmarking in medical image registration-review of the current state of the Learn2Reg challenge, Medical Imaging with Deep Learning , 2022.
Continuous benchmarking in medical image registration-review of the current state of the Learn2Reg challenge, Medical Imaging with Deep Learning , 2022.
Felix
Peisen,
Annika
Hänsch,
Alessa
Hering,
Andreas S
Brendlin,
Saif
Afat,
Konstantin
Nikolaou,
Sergios
Gatidis,
Thomas
Eigentler,
Teresa
Amaral,
Jan H
Moltz, and
others,
Combination of Whole-Body Baseline CT Radiomics and Clinical Parameters to Predict Response and Survival in a Stage-IV Melanoma Cohort Undergoing Immunotherapy, Cancers , vol. 14, no. 12, pp. 2992, 2022. Multidisciplinary Digital Publishing Institute.
Combination of Whole-Body Baseline CT Radiomics and Clinical Parameters to Predict Response and Survival in a Stage-IV Melanoma Cohort Undergoing Immunotherapy, Cancers , vol. 14, no. 12, pp. 2992, 2022. Multidisciplinary Digital Publishing Institute.
Daniel
Budelmann,
Hendrick
Laue,
Nick
Weiss,
Uta
Dahmen,
Lorenza A.
D’Alessandro,
Ina
Biermayer,
Ursula
Klingmüller,
Ahmed
Ghallab,
Reham
Hassan,
Brigitte
Begher-Tibbe,
Jan G.
Hengstler, and
Lars Ole
Schwen,
Automated Detection of Portal Fields and Central Veins in Whole-Slide Images of Liver Tissue, Journal of Pathology Informatics , vol. 13, pp. 100001, 2022.
Automated Detection of Portal Fields and Central Veins in Whole-Slide Images of Liver Tissue, Journal of Pathology Informatics , vol. 13, pp. 100001, 2022.
DOI: | https://doi.org/10.1016/j.jpi.2022.100001 |
File: | S2153353922000013 |
Bibtex: | @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} } |
N.
Kuete Meli,
F.
Mannel, and
J.
Lellmann,
An Iterative Quantum Approach for Transformation Estimation From Point Sets, in Computer Vision and Pattern Recognition , 2022. pp. 529--537.
An Iterative Quantum Approach for Transformation Estimation From Point Sets, in Computer Vision and Pattern Recognition , 2022. pp. 529--537.
Dominik
Hafemeyer, and
Florian
Mannel,
A path-following inexact Newton method for PDE-constrained optimal control in BV, COAP , vol. 82, no. 3, pp. 753--794, 2022.
A path-following inexact Newton method for PDE-constrained optimal control in BV, COAP , vol. 82, no. 3, pp. 753--794, 2022.
DOI: | 10.1007/s10589-022-00370-2 |
Bibtex: | @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}, } |
Florian
Mannel, and
Armin
Rund,
A hybrid semismooth quasi-Newton method for structured nonsmooth operator equations in Banach spaces, JoCA , vol. 29, no. 1, pp. 183--204, 2022.
A hybrid semismooth quasi-Newton method for structured nonsmooth operator equations in Banach spaces, JoCA , vol. 29, no. 1, pp. 183--204, 2022.
File: | jca29011.htm |
Bibtex: | @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}, } |
Sonja
Jäckle,
Tim
Eixmann,
Florian
Matysiak,
Malte M
Sieren,
Marco
Horn,
Hinnerk
Schulz-Hildebrandt,
Gereon
Hüttmann, and
Torben
Pätz,
3D Stent Graft Guidance Based on Tracking Systems, in Bildverarbeitung für die Medizin 2022 , Springer, 2022, pp. 253--253.
3D Stent Graft Guidance Based on Tracking Systems, in Bildverarbeitung für die Medizin 2022 , Springer, 2022, pp. 253--253.
2021
Alessa
Hering,
Felix
Peisen,
Teresa
Amaral,
Sergios
Gatidis,
Thomas
Eigentler,
Ahmed
Othman, and
Jan Hendrik
Moltz,
Whole-Body Soft-Tissue Lesion Tracking and Segmentation in Longitudinal CT Imaging Studies, in Medical Imaging with Deep Learning , 2021. pp. 312--326.
Whole-Body Soft-Tissue Lesion Tracking and Segmentation in Longitudinal CT Imaging Studies, in Medical Imaging with Deep Learning , 2021. pp. 312--326.
Kai Brehmer,
SqN: A Novel Distance Measure for Multiple Images and Applications, Institute of Mathematics and Image Computing, University of Lübeck, 2021.
SqN: A Novel Distance Measure for Multiple Images and Applications, Institute of Mathematics and Image Computing, University of Lübeck, 2021.
File: | K_Brehmer-Dissertation_SqN_final-online_publication_compressed.pdf |
Bibtex: | @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}, } |
Holger R
Roth,
Ziyue
Xu,
Carlos Tor
Diez,
Ramon Sanchez
Jacob,
Jonathan
Zember,
Jose
Molto,
Wenqi
Li,
Sheng
Xu,
Baris
Turkbey,
Evrim
Turkbey, and
others,
Rapid artificial intelligence solutions in a pandemic-the COVID-19-20 lung CT lesion segmentation challenge, Research Square , 2021. American Journal Experts.
Rapid artificial intelligence solutions in a pandemic-the COVID-19-20 lung CT lesion segmentation challenge, Research Square , 2021. American Journal Experts.
Florian Mannel,
On the order of convergence of Broyden’s method, Calcolo , vol. 58, no. 4, pp. 1--21, 2021.
On the order of convergence of Broyden’s method, Calcolo , vol. 58, no. 4, pp. 1--21, 2021.
DOI: | 10.1007/s10092-021-00441-6 |
Bibtex: | @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}, } |
Alessa
Hering,
Lasse
Hansen,
Tony CW
Mok,
Albert
Chung,
Hanna
Siebert,
Stephanie
Häger,
Annkristin
Lange,
Sven
Kuckertz,
Stefan
Heldmann,
Wei
Shao, and
others,
Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning, arXiv preprint arXiv:2112.04489 , 2021.
Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning, arXiv preprint arXiv:2112.04489 , 2021.
Journal of Mathematical Imaging and Vision, Special Issue on Scale Space and Variational Methods in Computer Vision,
Sonja
Jäckle,
Annkristin
Lange,
Verónica
García-Vázquez,
Tim
Eixmann,
Florian
Matysiak,
Malte Maria
Sieren,
Marco
Horn,
Hinnerk
Schulz-Hildebrandt,
Gereon
Hüttmann,
Floris
Ernst,
Stefan
Heldmann,
Torben
Pätz, and
Tobias
Preusser,
Instrument localisation for endovascular aneurysm repair: Comparison of two methods based on tracking systems or using imaging, The International Journal of Medical Robotics and Computer Assisted Surgery , vol. 17, no. 6, pp. e2327, 2021.
Instrument localisation for endovascular aneurysm repair: Comparison of two methods based on tracking systems or using imaging, The International Journal of Medical Robotics and Computer Assisted Surgery , vol. 17, no. 6, pp. e2327, 2021.
Alessa
Hering,
Stephanie
Häger,
Jan
Moltz,
Nikolas
Lessmann,
Stefan
Heldmann, and
Bram
Ginneken,
CNN-based lung CT registration with multiple anatomical constraints, Medical Image Analysis , vol. 72, pp. 102139, 2021. Elsevier.
CNN-based lung CT registration with multiple anatomical constraints, Medical Image Analysis , vol. 72, pp. 102139, 2021. Elsevier.
André
Homeyer,
Johannes
Lotz,
Lars Ole
Schwen,
Nick
Weiss,
Daniel
Romberg,
Henning
Höfener,
Norman
Zerbe, and
Peter
Hufnagl,
Artificial intelligence in pathology: From prototype to product, Journal of Pathology Informatics , vol. 12, no. 1, pp. 13, 2021. Elsevier BV.
Artificial intelligence in pathology: From prototype to product, Journal of Pathology Informatics , vol. 12, no. 1, pp. 13, 2021. Elsevier BV.
DOI: | 10.4103/jpi.jpi_84_20 |
File: | 10.4103%2Fjpi.jpi_84_20 |
Bibtex: | @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} } |
W.
Diepeveen, and
J.
Lellmann,
An Inexact Semismooth Newton Method on Riemannian Manifolds with Application to Duality-Based Total Variation Denoising, SIAM Journal on Imaging Sciences , vol. 14, no. 4, pp. 1565--1600, 2021.
An Inexact Semismooth Newton Method on Riemannian Manifolds with Application to Duality-Based Total Variation Denoising, SIAM Journal on Imaging Sciences , vol. 14, no. 4, pp. 1565--1600, 2021.
Sonja
Jäckle,
Veronica
Garcia-Vazquez,
Tim
Eixmann,
Florian
Matysiak,
Felix
Haxthausen,
Malte
Sieren,
Hinnerk
Schulz-Hildebrandt,
Gereon
Hüttmann,
Floris
Ernst,
Markus
Kleemann, and
Torben
Pätz,
Abstract: 3D Guidance Including Shape Sensing of a Stentgraft System, in Bildverarbeitung für die Medizin 2021 , Springer, 2021, pp. 34--34.
Abstract: 3D Guidance Including Shape Sensing of a Stentgraft System, in Bildverarbeitung für die Medizin 2021 , Springer, 2021, pp. 34--34.
DOI: | 10.1007/978-3-658-33198-6_9 |
File: | 10.1007%2F978-3-658-33198-6_9 |
Bibtex: | @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} } |
Sonja
Jäckle,
Elias
Röger,
Volker
Dicken,
Benjamin
Geisler,
Jakob
Schumacher, and
Max
Westphal,
A Statistical Model to Assess Risk for Supporting COVID-19 Quarantine Decisions, International Journal of Environmental Research and Public Health , vol. 18, no. 17, 2021.
A Statistical Model to Assess Risk for Supporting COVID-19 Quarantine Decisions, International Journal of Environmental Research and Public Health , vol. 18, no. 17, 2021.
DOI: | 10.3390/ijerph18179166 |
File: | 9166 |
Bibtex: | @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} } |
Sonja
Jäckle,
Tim
Eixmann,
Florian
Matysiak,
Malte Maria
Sieren,
Marco
Horn,
Hinnerk
Schulz-Hildebrandt,
Gereon
Hüttmann, and
Torben
Pätz,
3D Stent Graft Guidance based on Tracking Systems for Endovascular Aneurysm Repair, Current Directions in Biomedical Engineering , vol. 7, no. 1, pp. 17--20, 2021.
3D Stent Graft Guidance based on Tracking Systems for Endovascular Aneurysm Repair, Current Directions in Biomedical Engineering , vol. 7, no. 1, pp. 17--20, 2021.
DOI: | doi:10.1515/cdbme-2021-1004 |
File: | cdbme-2021-1004 |
Bibtex: | @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} } |
Alessa
Hering,
Annkristin
Lange,
Stefan
Heldmann,
Stephanie
Häger, and
Sven
Kuckertz,
Fraunhofer MEVIS Image Registration Solutions for the Learn2Reg 2021 Challenge, in International Conference on Medical Image Computing and Computer-Assisted Intervention , 2021. pp. 147--152.
Fraunhofer MEVIS Image Registration Solutions for the Learn2Reg 2021 Challenge, in International Conference on Medical Image Computing and Computer-Assisted Intervention , 2021. pp. 147--152.
2020
Annkristin
Lange, and
Stefan
Heldmann,
Multilevel 2D-3D Intensity-Based Image Registration, in International Workshop on Biomedical Image Registration , 2020. pp. 57--66.
Multilevel 2D-3D Intensity-Based Image Registration, in International Workshop on Biomedical Image Registration , 2020. pp. 57--66.
File: | 978-3-030-50120-4_6 |
Bibtex: | @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} } |
Annkristin
Lange, and
Stefan
Heldmann,
Intensity-Based 2D-3D Registration Using Normalized Gradient Fields, in Bildverarbeitung für die Medizin 2020 , Springer, 2020, pp. 163--168.
Intensity-Based 2D-3D Registration Using Normalized Gradient Fields, in Bildverarbeitung für die Medizin 2020 , Springer, 2020, pp. 163--168.
File: | 978-3-658-29267-6_33 |
Bibtex: | @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} } |
Sven
Kuckertz,
Nils
Papenberg,
Jonas
Honegger,
Tomasz
Morgas,
Benjamin
Haas, and
Stefan
Heldmann,
Learning Deformable Image Registration with Structure Guidance Constraints for Adaptive Radiotherapy, in International Workshop on Biomedical Image Registration , 2020. pp. 44--53.
Learning Deformable Image Registration with Structure Guidance Constraints for Adaptive Radiotherapy, in International Workshop on Biomedical Image Registration , 2020. pp. 44--53.
File: | 10.1007%2F978-3-030-50120-4_5 |
Bibtex: | @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} } |
Thomas Vogt,
Measure-Valued Variational Models with Applications in Image Processing, Institute of Mathematics and Image Computing, University of L\"ubeck, 2020.
Measure-Valued Variational Models with Applications in Image Processing, Institute of Mathematics and Image Computing, University of L\"ubeck, 2020.
File: | phd_thesis_vogt_small.pdf |
Bibtex: | @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}, } |
C.
Mercan,
G.C.A.M.
Mooij,
D.
Tellez,
J.
Lotz,
N.
Weiss,
M.
Gerven, and
F.
Ciompi,
Virtual Staining for Mitosis Detection in Breast Histopathology, IEEE, 2020.
Virtual Staining for Mitosis Detection in Breast Histopathology, IEEE, 2020.
File: | isbi45749.2020.9098409 |
Bibtex: | @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}, } |
MM
Sieren,
F
Brenne,
A
Hering,
H
Kienapfel,
N
Gebauer,
TH
Oechtering,
A
Fürschke,
F
Wegner,
E
Stahlberg,
S
Heldmann, and
others,
Rapid study assessment in follow-up whole-body computed tomography in patients with multiple myeloma using a dedicated bone subtraction software, European Radiology , vol. 30, no. 6, pp. 3198--3209, 2020. Springer.
Rapid study assessment in follow-up whole-body computed tomography in patients with multiple myeloma using a dedicated bone subtraction software, European Radiology , vol. 30, no. 6, pp. 3198--3209, 2020. Springer.
Sonja
Jäckle,
Verónica
García-Vázquez,
Tim
Eixmann,
Florian
Matysiak,
Haxthausen,
Malte Maria
Sieren,
Hinnerk
Schulz-Hildebrandt,
Gereon
Hüttmann,
Floris
Ernst,
Markus
Kleemann, and
Torben
Paetz,
Three-dimensional guidance including shape sensing of a stentgraft system for endovascular aneurysm repair, International Journal of Computer Assisted Radiology and Surgery , 2020.
Three-dimensional guidance including shape sensing of a stentgraft system for endovascular aneurysm repair, International Journal of Computer Assisted Radiology and Surgery , 2020.
File: | s11548-020-02167-2 |
Bibtex: | @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}, } |
Stephanie
Häger,
Stefan
Heldmann,
Alessa
Hering,
Sven
Kuckertz, and
Annkristin
Lange,
Variable fraunhofer MEVIS RegLib comprehensively applied to Learn2Reg challenge, in International Conference on Medical Image Computing and Computer-Assisted Intervention , 2020. pp. 74--79.
Variable fraunhofer MEVIS RegLib comprehensively applied to Learn2Reg challenge, in International Conference on Medical Image Computing and Computer-Assisted Intervention , 2020. pp. 74--79.
Sven
Kuckertz,
Nils
Papenberg,
Jonas
Honegger,
Tomasz
Morgas,
Benjamin
Haas, and
Stefan
Heldmann,
Deep learning based CT-CBCT image registration for adaptive radio therapy, in Medical Imaging 2020: Image Processing , 2020. pp. 113130Q.
Deep learning based CT-CBCT image registration for adaptive radio therapy, in Medical Imaging 2020: Image Processing , 2020. pp. 113130Q.
File: | 10.1117%2F12.2549531 |
Bibtex: | @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} } |
S.
Parisotto,
J.
Lellmann,
S.
Masnou, and
C.
Schönlieb,
Higher-Order Total Directional Variation: Imaging Applications, SIAM Journal on Imaging Sciences , vol. 13, no. 4, pp. 2063--2104, 2020.
Higher-Order Total Directional Variation: Imaging Applications, SIAM Journal on Imaging Sciences , vol. 13, no. 4, pp. 2063--2104, 2020.
Sven
Kuckertz,
Nils
Papenberg,
Jonas
Honegger,
Tomasz
Morgas,
Benjamin
Haas, and
Stefan
Heldmann,
Abstract: Deep Learning Based CT-CBCT Image Registration for Adaptive Radio Therapy, in Bildverarbeitung für die Medizin 2020 , Tolxdorff, Thomas and Deserno, Thomas M. and Handels, Heinz and Maier, Andreas and Maier-Hein, Klaus H. and Palm, Christoph, Eds. Springer, 2020. pp. 229--229.
Abstract: Deep Learning Based CT-CBCT Image Registration for Adaptive Radio Therapy, in Bildverarbeitung für die Medizin 2020 , Tolxdorff, Thomas and Deserno, Thomas M. and Handels, Heinz and Maier, Andreas and Maier-Hein, Klaus H. and Palm, Christoph, Eds. Springer, 2020. pp. 229--229.
ISBN: | 978-3-658-29267-6 |
File: | 978-3-658-29267-6_51 |
Bibtex: | @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} } |
Johannes Lotz,
Combined Local and Global Image Registration and its Application to Large-Scale Images in Digital Pathology, Institute of Mathematics and Image Computing, University of Lübeck, 2020.
Combined Local and Global Image Registration and its Application to Large-Scale Images in Digital Pathology, Institute of Mathematics and Image Computing, University of Lübeck, 2020.
Sonja
Jäckle,
Verónica
García-Vázquez,
Felix
Haxthausen,
Tim
Eixmann,
Malte Maria
Sieren,
Hinnerk
Schulz-Hildebrandt,
Gereon
Hüttmann,
Floris
Ernst,
Markus
Kleemann, and
Torben
Paetz,
3D catheter guidance including shape sensing for endovascular navigation, in Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling , Baowei Fei and Cristian A. Linte, Eds. SPIE, 2020. pp. 21 -- 29.
3D catheter guidance including shape sensing for endovascular navigation, in Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling , Baowei Fei and Cristian A. Linte, Eds. SPIE, 2020. pp. 21 -- 29.
DOI: | 10.1117/12.2548094 |
File: | 12.2548094 |
Bibtex: | @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} } |
Verónica
García-Vázquez,
Florian
Matysiak,
Sonja
Jäckle,
Tim
Eixmann,
Malte Maria
Sieren,
Felix
Haxthausen, and
Floris
Ernst,
Catheter pose-dependent virtual angioscopy images for endovascular aortic repair: validation with a video graphics array (VGA) camera, Current Directions in Biomedical Engineering , vol. 6, no. 1, 2020. De Gruyter.
Catheter pose-dependent virtual angioscopy images for endovascular aortic repair: validation with a video graphics array (VGA) camera, Current Directions in Biomedical Engineering , vol. 6, no. 1, 2020. De Gruyter.
V.
Corona,
J.
Lellmann,
P.
Nestor,
C.-B.
Sch\"onlieb, and
J.
Acosta-Cabronero,
A multi-contrast MRI approach to thalamus segmentation, Human Brain Mapping , 2020.
A multi-contrast MRI approach to thalamus segmentation, Human Brain Mapping , 2020.
Sonja
Jäckle,
Veronica
Garcia-Vazquez,
Felix
Haxthausen,
Tim
Eixmann,
Malte Maria
Sieren,
Hinnerk
Schulz-Hildebrandt,
Gereon
Hüttmann,
Floris
Ernst,
Markus
Kleemann, and
Torben
Pätz,
Abstract: 3D Catheter Guidance Including Shape Sensing for Endovascular Navigation, in Bildverarbeitung für die Medizin 2020 , Springer, 2020, pp. 261--261.
Abstract: 3D Catheter Guidance Including Shape Sensing for Endovascular Navigation, in Bildverarbeitung für die Medizin 2020 , Springer, 2020, pp. 261--261.
DOI: | 10.1007/978-3-658-29267-6_58 |
File: | 978-3-658-29267-6_58 |
Bibtex: | @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} } |
Thomas
Polzin,
Marc
Niethammer,
François-Xavier
Vialard, and
Jan
Modersitzki,
A discretize–optimize approach for LDDMM registration, in Riemannian Geometric Statistics in Medical Image Analysis , Xavier Pennec and Stefan Sommer and Tom Fletcher, Eds. Academic Press, 2020, pp. 479 - 532.
A discretize–optimize approach for LDDMM registration, in Riemannian Geometric Statistics in Medical Image Analysis , Xavier Pennec and Stefan Sommer and Tom Fletcher, Eds. Academic Press, 2020, pp. 479 - 532.
DOI: | https://doi.org/10.1016/B978-0-12-814725-2.00022-4 |
ISBN: | 978-0-12-814725-2 |
File: | B9780128147252000224 |
Bibtex: | @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." } |
Sonja
Jäckle,
Tim
Eixmann,
Hinnerk
Schulz-Hildebrandt,
Gereon
Hüttmann, and
Torben
Pätz,
Abstract: Fiber Optical Shape Sensing of Flexible Instruments, in Bildverarbeitung für die Medizin 2020 , Springer, 2020, pp. 314--314.
Abstract: Fiber Optical Shape Sensing of Flexible Instruments, in Bildverarbeitung für die Medizin 2020 , Springer, 2020, pp. 314--314.
DOI: | 10.1007/978-3-658-29267-6_70 |
File: | 978-3-658-29267-6_70 |
Bibtex: | @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} } |
Hari Om
Aggrawal, and
Jan
Modersitzki,
Accelerating the Registration of Image Sequences by Spatio-Temporal Multilevel Strategies, in Proceedings - International Symposium on Biomedical Imaging , IEEE Computer Society, 2020. pp. 683--686.
Accelerating the Registration of Image Sequences by Spatio-Temporal Multilevel Strategies, in Proceedings - International Symposium on Biomedical Imaging , IEEE Computer Society, 2020. pp. 683--686.
DOI: | {{10.1109/ISBI45749.2020.9098520}} |
File: | ISBI45749.2020.9098520}} |
Bibtex: | @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}}} } |
Hari Om
Aggrawal,
Martin S.
Andersen, and
Jan
Modersitzki,
An Image Registration Framework for Discontinuous Mappings Along Cracks, in International Workshop on Biomedical Image Registration , Springer, 2020. pp. 163--173.
An Image Registration Framework for Discontinuous Mappings Along Cracks, in International Workshop on Biomedical Image Registration , Springer, 2020. pp. 163--173.
DOI: | {{10.1007/978-3-030-50120-4_16}} |
File: | 978-3-030-50120-4_16}} |
Bibtex: | @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}}} } |
Jiří
Borovec,
Jan
Kybic,
Ignacio
Arganda-Carreras,
Dmitry V.
Sorokin,
Gloria
Bueno,
Alexander V.
Khvostikov,
Spyridon
Bakas,
Eric I-Chao
Chang,
Stefan
Heldmann,
Kimmo
Kartasalo,
Leena
Latonen,
Johannes
Lotz,
Michelle
Noga,
Sarthak
Pati,
Kumaradevan
Punithakumar,
Pekka
Ruusuvuori,
Andrzej
Skalski,
Nazanin
Tahmasebi,
Masi
Valkonen,
Ludovic
Venet,
Yizhe
Wang,
Nick
Weiss,
Marek
Wodzinski,
Yu
Xiang,
Yan
Xu,
Yan
Yan,
Paul
Yushkevic,
Shengyu
Zhao, and
Arrate
Muñoz-Barrutia,
ANHIR: Automatic Non-rigid Histological Image Registration Challenge, IEEE Transactions on Medical Imaging , 2020. IEEE.
ANHIR: Automatic Non-rigid Histological Image Registration Challenge, IEEE Transactions on Medical Imaging , 2020. IEEE.
File: | tmi.2020.2986331 |
Bianca
Lassen-Schmidt,
Alessa
Hering,
Stefan
Krass, and
Hans
Meine,
Automatic segmentation of the pulmonary lobes with a 3D u-net and optimized loss function, arXiv preprint arXiv:2006.00083 , 2020.
Automatic segmentation of the pulmonary lobes with a 3D u-net and optimized loss function, arXiv preprint arXiv:2006.00083 , 2020.
2019
Oliver
Klein,
Frederic
Kanter,
Hagen
Kulbe,
Paul
Jank,
Carsten
Denkert,
Grit
Nebrich,
Wolfgang D.
Schmitt,
Zhiyang
Wu,
Catarina A.
Kunze,
Jalid
Sehouli,
Silvia
Darb-Esfahani,
Ioana
Braicu,
Jan
Lellmann,
Herbert
Thiele, and
Eliane T.
Taube,
MALDI-Imaging for Classification of Epithelial Ovarian Cancer Histotypes from a Tissue Microarray Using Machine Learning Methods, PROTEOMICS – Clinical Applications , vol. 13, no. 1, pp. 1700181, 2019.
MALDI-Imaging for Classification of Epithelial Ovarian Cancer Histotypes from a Tissue Microarray Using Machine Learning Methods, PROTEOMICS – Clinical Applications , vol. 13, no. 1, pp. 1700181, 2019.
DOI: | 10.1002/prca.201700181 |
File: | prca.201700181 |
Bibtex: | @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} } |
Kai
Brehmer,
Hari Om
Aggrawal,
Stefan
Heldmann, and
Jan
Modersitzki,
Variational registration of multiple images with the SVD based SqN distance measure, in Scale Space and Variational Methods in Computer Vision: 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30-July 4, 2019, Proceedings , Burger, Martin and Lellmann, Jan and Modersitzki, Jan, Eds. Springer International Publishing, 2019. pp. 251--262.
Variational registration of multiple images with the SVD based SqN distance measure, in Scale Space and Variational Methods in Computer Vision: 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30-July 4, 2019, Proceedings , Burger, Martin and Lellmann, Jan and Modersitzki, Jan, Eds. Springer International Publishing, 2019. pp. 251--262.
DOI: | {{10.1007/978-3-030-22368-7_20}} |
File: | 1907.09732}} |
Bibtex: | @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}}} } |
Alessa
Hering, and
Stefan
Heldmann,
Unsupervised learning for large motion thoracic CT follow-up registration, in Medical Imaging 2019: Image Processing , 2019. pp. 331--337.
Unsupervised learning for large motion thoracic CT follow-up registration, in Medical Imaging 2019: Image Processing , 2019. pp. 331--337.
Alessa
Hering, and
Stefan
Heldmann,
Unsupervised learning for large motion thoracic CT follow-up registration, in Medical Imaging 2019: Image Processing , SPIE, 2019. pp. 1-7.
Unsupervised learning for large motion thoracic CT follow-up registration, in Medical Imaging 2019: Image Processing , SPIE, 2019. pp. 1-7.
DOI: | 10.1117/12.2506962 |
File: | 12.2506962 |
Bibtex: | @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} } |
Benjamin Wacker,
Two variants of magnetic diffusivity stabilized finite element methods for the magnetic induction equation, Mathematical Methods in the Applied Sciences , 2019. Wiley Online Library.
Two variants of magnetic diffusivity stabilized finite element methods for the magnetic induction equation, Mathematical Methods in the Applied Sciences , 2019. Wiley Online Library.
Sonja
Jäckle,
Jan
Strehlow, and
Stefan
Heldmann,
Shape Sensing with Fiber Bragg Grating Sensors, in Bildverarbeitung für die Medizin 2019 , Springer, 2019, pp. 258--263.
Shape Sensing with Fiber Bragg Grating Sensors, in Bildverarbeitung für die Medizin 2019 , Springer, 2019, pp. 258--263.
File: | 10.1007%2F978-3-658-25326-4_58 |
Bibtex: | @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}, } |
J.
Lellmann,
M.
Burger, and
J. (eds.)
Modersitzki,
Proceedings of the 7th International Conference On Scale Space and Variational Methods in Computer Vision (SSVM 2019)., .... Springer, 2019.
Proceedings of the 7th International Conference On Scale Space and Variational Methods in Computer Vision (SSVM 2019)., .... Springer, 2019.
Alessa
Hering,
Bram van
Ginneken, and
Stefan
Heldmann,
mlvirnet: Multilevel variational image registration network, in International Conference on Medical Image Computing and Computer-Assisted Intervention , 2019. pp. 257--265.
mlvirnet: Multilevel variational image registration network, in International Conference on Medical Image Computing and Computer-Assisted Intervention , 2019. pp. 257--265.
Alessa
Hering,
Bram
Ginneken, and
Stefan
Heldmann,
mlVIRNET: Multilevel Variational Image Registration Network, in Proceeding of Medical Image Computing and Computer Assisted Intervention (MICCAI 2019) , Springer, 2019. pp. 257-265.
mlVIRNET: Multilevel Variational Image Registration Network, in Proceeding of Medical Image Computing and Computer Assisted Intervention (MICCAI 2019) , Springer, 2019. pp. 257-265.
DOI: | 10.1007/978-3-030-32226-7_29 |
File: | 978-3-030-32226-7_29 |
Bibtex: | @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} } |
Alessa
Hering,
Sven
Kuckertz,
Stefan
Heldmann, and
Mattias P
Heinrich,
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, International journal of computer assisted radiology and surgery , vol. 14, no. 11, pp. 1901--1912, 2019. Springer.
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, International journal of computer assisted radiology and surgery , vol. 14, no. 11, pp. 1901--1912, 2019. Springer.
File: | s11548-019-02068-z |
Bibtex: | @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} } |
Sonja
Jäckle,
Tim
Eixmann,
Hinnerk
Schulz-Hildebrandt,
Gereon
Hüttmann, and
Torben
Pätz,
Fiber optical shape sensing of flexible instruments for endovascular navigation, International Journal of Computer Assisted Radiology and Surgery , vol. 14, no. 12, pp. 2137--2145, 2019.
Fiber optical shape sensing of flexible instruments for endovascular navigation, International Journal of Computer Assisted Radiology and Surgery , vol. 14, no. 12, pp. 2137--2145, 2019.
File: | s11548-019-02059-0 |
Bibtex: | @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}, } |
Thomas
Vogt,
Evgeny
Strekalovskiy,
Daniel
Cremers, and
Jan
Lellmann,
Lifting methods for manifold-valued variational problems, in Variational Methods for Nonlinear Geometric Data and Applications , Grohs, Philipp and Holler, Martin and Weinmann, Andreas, Eds. Springer International Publishing, 2019, pp. In press.
Lifting methods for manifold-valued variational problems, in Variational Methods for Nonlinear Geometric Data and Applications , Grohs, Philipp and Holler, Martin and Weinmann, Andreas, Eds. Springer International Publishing, 2019, pp. In press.
DOI: | {{10.1007/tba}} |
File: | 1908.03776.pdf}} |
Bibtex: | @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}}} } |
Thomas
Vogt, and
Jan
Lellmann,
Functional Liftings of Vectorial Variational Problems with Laplacian Regularization, in Scale Space and Variational Methods in Computer Vision: 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30-July 4, 2019, Proceedings , Burger, Martin and Lellmann, Jan and Modersitzki, Jan, Eds. Springer International Publishing, 2019. pp. 559--571.
Functional Liftings of Vectorial Variational Problems with Laplacian Regularization, in Scale Space and Variational Methods in Computer Vision: 7th International Conference, SSVM 2019, Hofgeismar, Germany, June 30-July 4, 2019, Proceedings , Burger, Martin and Lellmann, Jan and Modersitzki, Jan, Eds. Springer International Publishing, 2019. pp. 559--571.
DOI: | {{10.1007/978-3-030-22368-7_44}} |
File: | 1904.00898.pdf}} |
Bibtex: | @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}}} } |
Daniel
Budelmann,
Lars
König,
Nils
Papenberg, and
Jan
Lellmann,
Fully-Deformable 3D Image Registration in Two Seconds, in Bildverarbeitung für die Medizin 2019 , Handels, Heinz and Deserno, Thomas M. and Maier, Andreas and Maier-Hein, Klaus Hermann and Palm, Christoph and Tolxdorff, Thomas, Eds. Wiesbaden: Springer Fachmedien Wiesbaden, 2019. pp. 302--307.
Fully-Deformable 3D Image Registration in Two Seconds, in Bildverarbeitung für die Medizin 2019 , Handels, Heinz and Deserno, Thomas M. and Maier, Andreas and Maier-Hein, Klaus Hermann and Palm, Christoph and Tolxdorff, Thomas, Eds. Wiesbaden: Springer Fachmedien Wiesbaden, 2019. pp. 302--307.
Wouter
Bulten,
Péter
Bándi,
Jeffrey
Hoven,
Rob
Loo,
Johannes
Lotz,
Nick
Weiss,
Jeroen
Laak,
Bram
Ginneken,
Christina
Kaa, and
Geert
Litjens,
Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard, Scientific Reports , vol. 9, 2019.
Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard, Scientific Reports , vol. 9, 2019.
File: | s41598-018-37257-4 |
Bibtex: | @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}, } |
Alessa
Hering,
Sven
Kuckertz,
Stefan
Heldmann, and
Mattias P
Heinrich,
Enhancing label-driven deep deformable image registration with local distance metrics for state-of-the-art cardiac motion tracking, in Bildverarbeitung für die Medizin 2019 , Springer, 2019, pp. 309--314.
Enhancing label-driven deep deformable image registration with local distance metrics for state-of-the-art cardiac motion tracking, in Bildverarbeitung für die Medizin 2019 , Springer, 2019, pp. 309--314.
File: | 10.1007%2F978-3-658-25326-4_69 |
Bibtex: | @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}, } |
Hans
Meine, and
Alessa
Hering,
Efficient Prealignment of CT Scans for Registration through a Bodypart Regressor, arXiv preprint arXiv:1909.08898 , 2019.
Efficient Prealignment of CT Scans for Registration through a Bodypart Regressor, arXiv preprint arXiv:1909.08898 , 2019.
Hans
Meine, and
Alessa
Hering,
Efficient Prealignment of CT Scans for Registration through a Bodypart Regressor, in Proceedings of Medical Imaging with Deep Learning (MIDL 2019) , 2019. pp. 1-4.
Efficient Prealignment of CT Scans for Registration through a Bodypart Regressor, in Proceedings of Medical Imaging with Deep Learning (MIDL 2019) , 2019. pp. 1-4.
Felix
Haxthausen,
Sonja
Jäckle,
Jan
Strehlow,
Floris
Ernst, and
Veronica
García-Vazquez,
Catheter pose-dependent virtual angioscopy images visualized on augmented reality glasses, 2019. pp. 289-291.
Catheter pose-dependent virtual angioscopy images visualized on augmented reality glasses, 2019. pp. 289-291.
File: | cdbme-2019-0073.xml |
Bibtex: | @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} } |
Valentin
Kraft,
Jan
Strehlow,
Sonja
Jäckle,
Veronica
García-Vazquez,
Florian
Link,
Felix
Haxthausen,
Andrea
Schenk, and
Christian
Schumann,
A comparison of streaming methods for the Microsoft HoloLens, in Tagungsgband der 18. Jahrestagung der Deutschen Gesellschaft für Computer- und Roboterassistierte Chirurgie (CURAC) , Oliver Burgert, Hochschule Reutlingen, Bernhard Hirt, Universität Tübingen, 2019. pp. 212-216.
A comparison of streaming methods for the Microsoft HoloLens, in Tagungsgband der 18. Jahrestagung der Deutschen Gesellschaft für Computer- und Roboterassistierte Chirurgie (CURAC) , Oliver Burgert, Hochschule Reutlingen, Bernhard Hirt, Universität Tübingen, 2019. pp. 212-216.
O.
Klein,
F.
Kanter,
H.
Kulbe,
P.
Jank,
C.
Denkert,
G.
Nebrich,
W.D.
Schmitt,
Z.
Wu,
C.A.
Kunze,
J.
Sehouli,
S.
Darb-Eshfahani,
I.
Braicu,
J.
Lellmann,
H.
Thiele, and
E.T.
Taube,
{MALDI}-Imaging for Classification of Epithelial Ovarian Cancer Histotypes from a Tissue Microarray Using Machine Learning Methods, Proteomics Clinical Applications , vol. 13, no. 1, pp. 1700181, 2019.
{MALDI}-Imaging for Classification of Epithelial Ovarian Cancer Histotypes from a Tissue Microarray Using Machine Learning Methods, Proteomics Clinical Applications , vol. 13, no. 1, pp. 1700181, 2019.
2018
T.
Vogt, and
J.
Lellmann,
Measure-Valued Variational Models with Applications to Diffusion-Weighted Imaging, Journal of Mathematical Imaging and Vision , 2018. Springer International Publishing.
Measure-Valued Variational Models with Applications to Diffusion-Weighted Imaging, Journal of Mathematical Imaging and Vision , 2018. Springer International Publishing.
DOI: | 10.1007/s10851-018-0827-8 |
File: | VogtLellmann_JMIV2018_manuscript_01.pdf |
Bibtex: | @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} } |
Lars König,
Matrix-free approaches for deformable image registration with large-scale and real-time applications in medical imaging, Institute of Mathematics and Image Computing, University of Lübeck, 2018.
Matrix-free approaches for deformable image registration with large-scale and real-time applications in medical imaging, Institute of Mathematics and Image Computing, University of Lübeck, 2018.
File: | lkoenig-dissertation_compressed.pdf |
Bibtex: | @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}, } |
Kai
Brehmer,
Benjamin
Wacker, and
Jan
Modersitzki,
Simultaneous Registration of Image Sequences--a novel singular value based images similarity measure, PAMM , vol. 18, no. 1, pp. e201800370, 2018. Wiley Online Library.
Simultaneous Registration of Image Sequences--a novel singular value based images similarity measure, PAMM , vol. 18, no. 1, pp. e201800370, 2018. Wiley Online Library.
DOI: | {{10.1002/pamm.201800370}} |
File: | 1907.09275}} |
Bibtex: | @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} } |
Sonja
Jäckle, and
Stefan
Heldmann,
Rigid Lens - Locally Rigid Approximations of Deformable Registration for Change Assessment in Thorax-Abdomen CT Follow-Up Scans, in Image Analysis for Moving Organ, Breast, and Thoracic Images , Springer, 2018, pp. 272--283.
Rigid Lens - Locally Rigid Approximations of Deformable Registration for Change Assessment in Thorax-Abdomen CT Follow-Up Scans, in Image Analysis for Moving Organ, Breast, and Thoracic Images , Springer, 2018, pp. 272--283.
File: | 978-3-030-00946-5_27 |
Bibtex: | @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}, } |
Veronica
García-Vazquez,
Felix
Haxthausen,
Sonja
Jäckle,
Christian
Schumann,
Ivo
Kuhlemann,
Juljan
Bouchagiar,
Anna-Catharina
Höfer,
Florian
Matysiak,
Gereon
Hüttmann,
Jan Peter
Goltz, and
others,
Navigation and visualisation with HoloLens in endovascular aortic repair, Innovative Surgical Sciences , vol. 3, no. 3, pp. 167--177, 2018. De Gruyter.
Navigation and visualisation with HoloLens in endovascular aortic repair, Innovative Surgical Sciences , vol. 3, no. 3, pp. 167--177, 2018. De Gruyter.
File: | iss-2018-2001.pdf |
Bibtex: | @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} } |
Benedikt
Loewenhauser, and
Jan
Lellmann,
Functional Lifting for Variational Problems with Higher-Order, Imaging, Vision and Learning Based on Optimization and PDEs: IVLOPDE, Bergen, Norway, August 29--September 2, 2016 , pp. 101, 2018. Springer.
Functional Lifting for Variational Problems with Higher-Order, Imaging, Vision and Learning Based on Optimization and PDEs: IVLOPDE, Bergen, Norway, August 29--September 2, 2016 , pp. 101, 2018. Springer.
File: | 10.1007%2F978-3-319-91274-5_5 |
Bibtex: | @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} } |
Thomas Polzin,
Large Deformation Diffeomorphic Metric Mappings - Theory, Numerics, and Applications, Institute of Mathematics and Image Computing, University of Lübeck, 2018.
Large Deformation Diffeomorphic Metric Mappings - Theory, Numerics, and Applications, Institute of Mathematics and Image Computing, University of Lübeck, 2018.
File: | 20180610_Diss_Thomas_Polzin_LDDMM_onlineVersion_comp.pdf |
Bibtex: | @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}, } |
Erik A
Hanson,
Constantin
Sandmann,
Alexander
Malyshev,
Arvid
Lundervold,
Jan
Modersitzki, and
Erlend
Hodneland,
Estimating the discretization dependent accuracy of perfusion in coupled capillary flow measurements, PloS one , vol. 13, no. 7, pp. e0200521, 2018. Public Library of Science.
Estimating the discretization dependent accuracy of perfusion in coupled capillary flow measurements, PloS one , vol. 13, no. 7, pp. e0200521, 2018. Public Library of Science.
Alexander Oliver
Mader,
Cristian
Lorenz,
Martin
Bergtholdt,
Jens
Berg,
Hauke
Schramm,
Jan
Modersitzki, and
Carsten
Meyer,
Detection and localization of spatially correlated point landmarks in medical images using an automatically learned conditional random field, Computer Vision and Image Understanding , vol. 176, pp. 45--53, 2018. Elsevier.
Detection and localization of spatially correlated point landmarks in medical images using an automatically learned conditional random field, Computer Vision and Image Understanding , vol. 176, pp. 45--53, 2018. Elsevier.
Kai
Brehmer,
Benjamin
Wacker, and
Jan
Modersitzki,
A Novel Similarity Measure for Image Sequences, in International Workshop on Biomedical Image Registration , 2018. pp. 47--56.
A Novel Similarity Measure for Image Sequences, in International Workshop on Biomedical Image Registration , 2018. pp. 47--56.
DOI: | {{10.1007/978-3-319-92258-4_5}} |
File: | 1907.09741}} |
Bibtex: | @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}}} } |
Lars
König,
Jan
Rühaak,
Alexander
Derksen, and
Jan
Lellmann,
A matrix-free approach to parallel and memory-efficient deformable image registration, SIAM Journal on Scientific Computing , vol. 40, no. 3, pp. B858--B888, 2018.
A matrix-free approach to parallel and memory-efficient deformable image registration, SIAM Journal on Scientific Computing , vol. 40, no. 3, pp. B858--B888, 2018.
DOI: | 10.1137/17M1125522 |
File: | konig2018matrix.pdf |
Bibtex: | @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} } |
2017
Constantin M. Sandmann,
Dynamic Models and Coupling in Medical 4D Imaging, Institute of Mathematics and Image Computing, University of Lübeck, 2017.
Dynamic Models and Coupling in Medical 4D Imaging, Institute of Mathematics and Image Computing, University of Lübeck, 2017.
File: | ediss1862.pdf |
Bibtex: | @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}, } |
Y.
Korolev, and
J.
Lellmann,
"Image reconstruction with imperfect forward models and applications in deblurring" 2017.
"Image reconstruction with imperfect forward models and applications in deblurring" 2017.
File: | 1708.01244 |
Bibtex: | @TechReport{KorolevLellmann2017, author = {Korolev, Y. and Lellmann, J.}, title = {Image reconstruction with imperfect forward models and applications in deblurring}, institution = {University of Luebeck}, year = {2017}, type = {Preprint}, number = {arXiv:1708.01244}, url = {https://arxiv.org/abs/1708.01244} } |
Jan
Rühaak,
Thomas
Polzin,
Stefan
Heldmann,
Ivor J. A.
Simpson,
Heinz
Handels,
Jan
Modersitzki, and
Mattias P.
Heinrich,
Estimation of Large Motion in Lung CT by Integrating Regularized Keypoint Correspondences into Dense Deformable Registration, IEEE Transactions on Medical Imaging , vol. 36, no. 8, pp. 1746--1757, 2017. IEEE.
Estimation of Large Motion in Lung CT by Integrating Regularized Keypoint Correspondences into Dense Deformable Registration, IEEE Transactions on Medical Imaging , vol. 36, no. 8, pp. 1746--1757, 2017. IEEE.
Thomas
Vogt, and
Jan
Lellmann,
An Optimal Transport-Based Restoration Method for Q-Ball Imaging, in Scale Space and Variational Methods in Computer Vision: 6th International Conference, SSVM 2017, Kolding, Denmark, June 4-8, 2017, Proceedings , Lauze, Francois and Dong, Yiqiu and Dahl, Anders Bjorholm, Eds. Springer International Publishing, 2017. pp. 271--282.
An Optimal Transport-Based Restoration Method for Q-Ball Imaging, in Scale Space and Variational Methods in Computer Vision: 6th International Conference, SSVM 2017, Kolding, Denmark, June 4-8, 2017, Proceedings , Lauze, Francois and Dong, Yiqiu and Dahl, Anders Bjorholm, Eds. Springer International Publishing, 2017. pp. 271--282.
DOI: | {{10.1007/978-3-319-58771-4_22}} |
File: | VogtLellmann_SSVM2017_Preprint.pdf |
Bibtex: | @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}}} } |
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