2024
Jakob
Schumacher,
Lisa
Kühne,
Sophia
Brüssermann,
Benjamin
Geisler, and
Sonja
Jäckle,
COVID-19 isolation and quarantine orders in Berlin-Reinickendorf (Germany): How many, how long and to whom?, Plos one , vol. 19, no. 3, pp. e0271848, 2024. Public Library of Science San Francisco, CA USA.
COVID-19 isolation and quarantine orders in Berlin-Reinickendorf (Germany): How many, how long and to whom?, Plos one , vol. 19, no. 3, pp. e0271848, 2024. Public Library of Science San Francisco, CA USA.
File: | Dateilink |
Bibtex: | ![]() @article{schumacher2024covid, title={COVID-19 isolation and quarantine orders in Berlin-Reinickendorf (Germany): How many, how long and to whom?}, author={Schumacher, Jakob and Kühne, Lisa and Brüssermann, Sophia and Geisler, Benjamin and Jäckle, Sonja}, journal={Plos one}, volume={19}, number={3}, pages={e0271848}, year={2024}, publisher={Public Library of Science San Francisco, CA USA} } |
Johannes
Bostelmann,
Ole
Gildemeister, and
Jan
Lellmann,
Stationary Velocity Fields on Matrix Groups for Deformable Image Registration, arXiv preprint arXiv:2410.10997 , 2024.
Stationary Velocity Fields on Matrix Groups for Deformable Image Registration, arXiv preprint arXiv:2410.10997 , 2024.
File: | Dateilink |
Bibtex: | ![]() @article{bostelmann2024stationary, title={Stationary Velocity Fields on Matrix Groups for Deformable Image Registration}, author={Bostelmann, Johannes and Gildemeister, Ole and Lellmann, Jan}, journal={arXiv preprint arXiv:2410.10997}, year={2024} } |
Danielle Bednarski,
Functional Lifting: Nonlinear Inverse Scale Space Iterations and Neural Fields, Universität zu Lübeck, 2024.
Functional Lifting: Nonlinear Inverse Scale Space Iterations and Neural Fields, Universität zu Lübeck, 2024.
File: | Dateilink |
Boqiang
Huang,
Jiayu
Ying,
Ruizhi
Lyu,
Nadine S.
Schaadt,
Barbara M.
Klinkhammer,
Peter
Boor,
Johannes
Lotz,
Friedrich
Feuerhake, and
Dorit
Merhof,
Utnetpara: A Hybrid CNN-Transformer Architecture with Multi-Scale Fusion for Whole-Slide Image Segmentation, in 2024 IEEE International Symposium on Biomedical Imaging (ISBI) , 2024. pp. 1-5.
Utnetpara: A Hybrid CNN-Transformer Architecture with Multi-Scale Fusion for Whole-Slide Image Segmentation, in 2024 IEEE International Symposium on Biomedical Imaging (ISBI) , 2024. pp. 1-5.
DOI: | 10.1109/ISBI56570.2024.10635778 |
Kai
Geißler,
Daniel
Mensing,
Markus
Wenzel,
Jochen G.
Hirsch, and
Stefan
Heldmann,
Towards TotalSegmentator for MRI data leveraging GIN data augmentation, in Medical Imaging 2024: Image Processing , Olivier Colliot and Jhimli Mitra, Eds. SPIE, 2024. pp. 1292604.
Towards TotalSegmentator for MRI data leveraging GIN data augmentation, in Medical Imaging 2024: Image Processing , Olivier Colliot and Jhimli Mitra, Eds. SPIE, 2024. pp. 1292604.
Till
Nicke,
Jan Raphael
Schaefer,
Henning
Hoefener,
Friedrich
Feuerhake,
Dorit
Merhof,
Fabian
Kiessling, and
Johannes
Lotz,
Tissue Concepts: supervised foundation models in computational pathology, arXiv preprint arXiv:2409.03519 , 2024.
Tissue Concepts: supervised foundation models in computational pathology, arXiv preprint arXiv:2409.03519 , 2024.
File: | Dateilink |
Bibtex: | ![]() @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}, } |
Philippe
Weitz,
Masi
Valkonen,
Leslie
Solorzano,
Circe
Carr,
Kimmo
Kartasalo,
Constance
Boissin,
Sonja
Koivukoski,
Aino
Kuusela,
Dusan
Rasic,
Yanbo
Feng,
Sandra Sinius
Pouplier,
Abhinav
Sharma,
Kajsa Ledesma
Eriksson,
Stephanie
Robertson,
Christian
Marzahl,
Chandler D.
Gatenbee,
Alexander R.A.
Anderson,
Marek
Wodzinski,
Artur
Jurgas,
Niccolò
Marini,
Manfredo
Atzori,
Henning
Müller,
Daniel
Budelmann,
Nick
Weiss,
Stefan
Heldmann,
Johannes
Lotz,
Jelmer M.
Wolterink,
Bruno {De
Santi},
Abhijeet
Patil,
Amit
Sethi,
Satoshi
Kondo,
Satoshi
Kasai,
Kousuke
Hirasawa,
Mahtab
Farrokh,
Neeraj
Kumar,
Russell
Greiner,
Leena
Latonen,
Anne-Vibeke
Laenkholm,
Johan
Hartman,
Pekka
Ruusuvuori, and
Mattias
Rantalainen,
The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue, Medical Image Analysis , vol. 97, pp. 103257, 2024.
The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue, Medical Image Analysis , vol. 97, pp. 103257, 2024.
File: | Dateilink |
Bibtex: | ![]() @article{WeitzEtAl2024, author = {Philippe Weitz and Masi Valkonen and Leslie Solorzano and Circe Carr and Kimmo Kartasalo and Constance Boissin and Sonja Koivukoski and Aino Kuusela and Dusan Rasic and Yanbo Feng and Sandra Sinius Pouplier and Abhinav Sharma and Kajsa Ledesma Eriksson and Stephanie Robertson and Christian Marzahl and Chandler D. Gatenbee and Alexander R.A. Anderson and Marek Wodzinski and Artur Jurgas and Niccolò Marini and Manfredo Atzori and Henning Müller and Daniel Budelmann and Nick Weiss and Stefan Heldmann and Johannes Lotz and Jelmer M. Wolterink and Bruno {De Santi} and Abhijeet Patil and Amit Sethi and Satoshi Kondo and Satoshi Kasai and Kousuke Hirasawa and Mahtab Farrokh and Neeraj Kumar and Russell Greiner and Leena Latonen and Anne-Vibeke Laenkholm and Johan Hartman and Pekka Ruusuvuori and Mattias Rantalainen}, journal = {Medical Image Analysis}, pages = {103257}, title = {The ACROBAT 2022 challenge: Automatic registration of breast cancer tissue}, volume = {97}, year = {2024}} |
Kai
Geißler,
Jochen G.
Hirsch,
Stefan
Heldmann, and
Hans
Meine,
Structure Size as Confounder in Uncertainty Based Segmentation Quality Prediction, in Medical Imaging with Deep Learning , 2024.
Structure Size as Confounder in Uncertainty Based Segmentation Quality Prediction, in Medical Imaging with Deep Learning , 2024.
File: | Dateilink |
Bibtex: | ![]() @inproceedings{GeißlerEtl2024, author = {Kai Geißler and Jochen G. Hirsch and Stefan Heldmann and Hans Meine}, booktitle = {Medical Imaging with Deep Learning}, title = {Structure Size as Confounder in Uncertainty Based Segmentation Quality Prediction}, year = {2024}} |
Saskia
Neuber,
Pia F
Schulz,
Sven
Kuckertz, and
Jan
Modersitzki,
Segmentation-inspired Image Registration, in Bildverarbeitung für die Medizin 2024: Proceedings, German Conference on Medical Image Computing, Erlangen, March 10-12, 2024 , 2024. pp. 205.
Segmentation-inspired Image Registration, in Bildverarbeitung für die Medizin 2024: Proceedings, German Conference on Medical Image Computing, Erlangen, March 10-12, 2024 , 2024. pp. 205.
File: | Dateilink |
Bibtex: | ![]() @inproceedings{neuber2024segmentation, title={Segmentation-inspired Image Registration}, author={Neuber, Saskia and Schulz, Pia F and Kuckertz, Sven and Modersitzki, Jan}, booktitle={Bildverarbeitung für die Medizin 2024: Proceedings, German Conference on Medical Image Computing, Erlangen, March 10-12, 2024}, pages={205}, year={2024}, organization={Springer-Verlag} } |
Willem
Diepeveen,
Carlos
Esteve-Yagüe,
Jan
Lellmann,
Ozan
Öktem, and
Carola-Bibiane
Schönlieb,
Riemannian geometry for efficient analysis of protein dynamics data, Proceedings of the National Academy of Sciences , vol. 121, no. 33, pp. e2318951121, 2024. National Academy of Sciences.
Riemannian geometry for efficient analysis of protein dynamics data, Proceedings of the National Academy of Sciences , vol. 121, no. 33, pp. e2318951121, 2024. National Academy of Sciences.
File: | Dateilink |
Bibtex: | ![]() @article{diepeveen2024riemannian, title={Riemannian geometry for efficient analysis of protein dynamics data}, author={Diepeveen, Willem and Esteve-Yagüe, Carlos and Lellmann, Jan and Öktem, Ozan and Schönlieb, Carola-Bibiane}, journal={Proceedings of the National Academy of Sciences}, volume={121}, number={33}, pages={e2318951121}, year={2024}, publisher={National Academy of Sciences} } |
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} } |
Raphael
Schäfer,
Till
Nicke,
Henning
Höfener,
Annkristin
Lange,
Dorit
Merhof,
Friedrich
Feuerhake,
Volkmar
Schulz,
Johannes
Lotz, and
Fabian
Kiessling,
Overcoming data scarcity in biomedical imaging with a foundational multi-task model, Nature Computational Science , vol. 4, no. 7, pp. 495--509, 2024. Nature Publishing Group US New York.
Overcoming data scarcity in biomedical imaging with a foundational multi-task model, Nature Computational Science , vol. 4, no. 7, pp. 495--509, 2024. Nature Publishing Group US New York.
File: | Dateilink |
Bibtex: | ![]() @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} } |
Johanna
Brosig,
Nina
Krüger,
Inna
Khasyanova,
Isaac
Wamala,
Matthias
Ivantsits,
Simon
Sündermann,
Jörg
Kempfert,
Stefan
Heldmann, and
Anja
Hennemuth,
Learning three-dimensional aortic root assessment based on sparse annotations, Journal of Medical Imaging , vol. 11, no. 4, pp. 044504, 2024.
Learning three-dimensional aortic root assessment based on sparse annotations, Journal of Medical Imaging , vol. 11, no. 4, pp. 044504, 2024.
File: | Dateilink |
Bibtex: | ![]() @article{BrosigEtAl2024b, author = {Johanna Brosig and Nina Krüger and Inna Khasyanova and Isaac Wamala and Matthias Ivantsits and Simon Sündermann and Jörg Kempfert and Stefan Heldmann and Anja Hennemuth}, journal = {Journal of Medical Imaging}, number = {4}, pages = {044504}, title = {Learning three-dimensional aortic root assessment based on sparse annotations}, volume = {11}, year = {2024}} |
Johanna
Brosig,
Nina
Krüger,
Isaac
Wamala,
Matthias
Ivantsits,
Simon
Sündermann,
Jörg
Kempfert,
Stefan
Heldmann, and
Anja
Hennemuth,
Learning 3D aortic root assessment based on sparse annotations, in Medical Imaging 2024: Computer-Aided Diagnosis , Weijie Chen and Susan M. Astley, Eds. SPIE, 2024. pp. 129271S.
Learning 3D aortic root assessment based on sparse annotations, in Medical Imaging 2024: Computer-Aided Diagnosis , Weijie Chen and Susan M. Astley, Eds. SPIE, 2024. pp. 129271S.
Temke
Kohlbrandt,
Jan
Moltz,
Stefan
Heldmann,
Alessa
Hering, and
Jan
Lellmann,
Joint Learning of Image Registration and Change Detection for Lung CT Images, in Bildverarbeitung für die Medizin 2024 , Maier, Andreas and Deserno, Thomas M. and Handels, Heinz and Maier-Hein, Klaus and Palm, Christoph and Tolxdorff, Thomas, Eds. Wiesbaden: Springer Fachmedien Wiesbaden, 2024. pp. 46--51.
Joint Learning of Image Registration and Change Detection for Lung CT Images, in Bildverarbeitung für die Medizin 2024 , Maier, Andreas and Deserno, Thomas M. and Handels, Heinz and Maier-Hein, Klaus and Palm, Christoph and Tolxdorff, Thomas, Eds. Wiesbaden: Springer Fachmedien Wiesbaden, 2024. pp. 46--51.
File: | Dateilink |
Bibtex: | ![]() @inproceedings{KohlbrandtEtAl2024, address = {Wiesbaden}, author = {Kohlbrandt, Temke and Moltz, Jan and Heldmann, Stefan and Hering, Alessa and Lellmann, Jan}, booktitle = {Bildverarbeitung für die Medizin 2024}, editor = {Maier, Andreas and Deserno, Thomas M. and Handels, Heinz and Maier-Hein, Klaus and Palm, Christoph and Tolxdorff, Thomas}, pages = {46--51}, publisher = {Springer Fachmedien Wiesbaden}, title = {Joint Learning of Image Registration and Change Detection for Lung CT Images}, year = {2024}} |
Anna
Rörich,
Annkristin
Lange,
Stefan
Heldmann,
Jan Hendrik
Moltz,
Lars
Walczak,
Sinef
Yarar-Schlickewei,
Felix
Güttler, and
Joachim
Georgii,
Inferring 3D finger bone shapes from 2D images -- a detailed analysis of shape accuracy, Computer Methods in Biomechanics and Biomedical Engineering: Imaging \& Visualization , vol. 12, no. 1, pp. 2359397, 2024.
Inferring 3D finger bone shapes from 2D images -- a detailed analysis of shape accuracy, Computer Methods in Biomechanics and Biomedical Engineering: Imaging \& Visualization , vol. 12, no. 1, pp. 2359397, 2024.
File: | Dateilink |
Bibtex: | ![]() @article{RoerichEtAl2024, author = {Anna Rörich and Annkristin Lange and Stefan Heldmann and Jan Hendrik Moltz and Lars Walczak and Sinef Yarar-Schlickewei and Felix Güttler and Joachim Georgii}, journal = {Computer Methods in Biomechanics and Biomedical Engineering: Imaging \& Visualization}, number = {1}, pages = {2359397}, title = {Inferring 3D finger bone shapes from 2D images -- a detailed analysis of shape accuracy}, volume = {12}, year = {2024}} |
Sina
Walluscheck,
Annika
Gerken,
Ivana
Galinovic,
Kersten
Villringer,
Jochen B.
Fiebach,
Jan
Klein, and
Stefan
Heldmann,
Generative adversarial network--based reconstruction of healthy anatomy for anomaly detection in brain CT scans, Journal of Medical Imaging , no. 4, pp. 044508, 2024.
Generative adversarial network--based reconstruction of healthy anatomy for anomaly detection in brain CT scans, Journal of Medical Imaging , no. 4, pp. 044508, 2024.
File: | Dateilink |
Bibtex: | ![]() @article{WalluscheckEtAl2024, author = {Sina Walluscheck and Annika Gerken and Ivana Galinovic and Kersten Villringer and Jochen B. Fiebach and Jan Klein and Stefan Heldmann}, journal = {Journal of Medical Imaging}, number = {4}, pages = {044508}, title = {Generative adversarial network--based reconstruction of healthy anatomy for anomaly detection in brain CT scans}}, volume = {11}, year = {2024} |
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}, } |
Nassim
Bouteldja,
David Laurin
Hölscher,
Barbara Mara
Klinkhammer,
Roman David
Buelow,
Johannes
Lotz,
Nick
Weiss,
Christoph
Daniel,
Kerstin
Amann, and
Peter
Boor,
Stain-Independent Deep Learning–Based Analysis of Digital Kidney Histopathology, The American Journal of Pathology , vol. 193, no. 1, pp. 73-83, 2023.
Stain-Independent Deep Learning–Based Analysis of Digital Kidney Histopathology, The American Journal of Pathology , vol. 193, no. 1, pp. 73-83, 2023.
DOI: | https://doi.org/10.1016/j.ajpath.2022.09.011 |
File: | S0002944022003212 |
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.
Maryam
Berijanian,
Nadine S.
Schaadt,
Boqiang
Huang,
Johannes
Lotz,
Friedrich
Feuerhake, and
Dorit
Merhof,
Unsupervised many-to-many stain translation for histological image augmentation to improve classification accuracy, Journal of Pathology Informatics , vol. 14, pp. 100195, 2023.
Unsupervised many-to-many stain translation for histological image augmentation to improve classification accuracy, Journal of Pathology Informatics , vol. 14, pp. 100195, 2023.
DOI: | https://doi.org/10.1016/j.jpi.2023.100195 |
File: | S2153353923000093 |
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: | |
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}, } |
Ruqayya
Awan,
Shan E. Ahmed
Raza,
Johannes
Lotz,
Nick
Weiss, and
Nasir
Rajpoot,
Deep feature based cross-slide registration, Computerized Medical Imaging and Graphics , vol. 104, pp. 102162, 2023.
Deep feature based cross-slide registration, Computerized Medical Imaging and Graphics , vol. 104, pp. 102162, 2023.
DOI: | https://doi.org/10.1016/j.compmedimag.2022.102162 |
File: | S089561112200132X |
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.
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.
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.
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.
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.
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}, } |
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.
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: | |
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
Journal of Mathematical Imaging and Vision, Special Issue on Scale Space and Variational Methods in Computer Vision,
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: | |
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.
Maschenka CA.
Balkenhol,
Francesco
Ciompi,
Żaneta
Świderska-Chadaj,
Rob {van
Loo},
Milad
Intezar,
Irene
Otte-Höller,
Daan
Geijs,
Johannes
Lotz,
Nick
Weiss,
Thomas {de
Bel},
Geert
Litjens,
Peter
Bult, and
Jeroen AWM. {van
Laak},
Optimized tumour infiltrating lymphocyte assessment for triple negative breast cancer prognostics, The Breast , vol. 56, pp. 78-87, 2021.
Optimized tumour infiltrating lymphocyte assessment for triple negative breast cancer prognostics, The Breast , vol. 56, pp. 78-87, 2021.
DOI: | https://doi.org/10.1016/j.breast.2021.02.007 |
File: | S0960977621000217 |
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.
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,
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.
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,
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} } |
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: | https://doi.org/10.4103/jpi.jpi_84_20 |
File: | S2153353922001353 |
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} } |
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.
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
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, in 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI) , IEEE, 2020. pp. 1770-1774.
Virtual Staining for Mitosis Detection in Breast Histopathology, in 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI) , IEEE, 2020. pp. 1770-1774.
DOI: | 10.1109/ISBI45749.2020.9098409 |
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}, } |
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.
File: | |
Bibtex: | ![]() @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}, } |
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}, } |
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.
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} } |
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: | |
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}, } |
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} } |
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} } |
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.
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} } |
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.
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} } |
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.
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." } |
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,
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} } |
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} } |
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
Yushkevich,
Shengyu
Zhao, and
Arrate
Muñoz-Barrutia,
ANHIR: Automatic Non-Rigid Histological Image Registration Challenge, IEEE Transactions on Medical Imaging , vol. 39, no. 10, pp. 3042-3052, 2020. IEEE.
ANHIR: Automatic Non-Rigid Histological Image Registration Challenge, IEEE Transactions on Medical Imaging , vol. 39, no. 10, pp. 3042-3052, 2020. IEEE.
DOI: | 10.1109/TMI.2020.2986331 |
File: | tmi.2020.2986331 |
2019
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}}} } |
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
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} } |
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} } |
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.
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}}} } |
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.
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.
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.
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} } |
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.
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.

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