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2020 – today
- 2024
[c22]Laura Pfaff, Fabian Wagner, Julian Hossbach, Elisabeth Preuhs, Mareike Thies, Felix Denzinger, Dominik Nickel, Tobias Würfl, Andreas K. Maier:
Abstract: Robust Multi-contrast MRI Denoising using Trainable Bilateral Filters without Noise-free Targets. Bildverarbeitung für die Medizin 2024: 26- [c21]Laura Pfaff, Fabian Wagner, Nastassia Vysotskaya, Mareike Thies, Noah Maul, Siyuan Mei, Tobias Würfl, Andreas K. Maier:
No-New-Denoiser: A Critical Analysis of Diffusion Models for Medical Image Denoising. MICCAI (10) 2024: 568-578 - 2023
- [c20]Laura Pfaff, Fabian Wagner, Julian Hossbach, Elisabeth Preuhs, Noah Maul, Mareike Thies, Felix Denzinger, Dominik Nickel
, Tobias Würfl, Andreas Maier:
Robust Multi-Contrast Mri Denoising Using Trainable Bilateral Filters Without Noise-Free Targets. ISBI 2023: 1-5 - 2022
- [e3]Nandinee Fariah Haq, Patricia Johnson, Andreas Maier, Chen Qin, Tobias Würfl, Jaejun Yoo:
Machine Learning for Medical Image Reconstruction - 5th International Workshop, MLMIR 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings. Lecture Notes in Computer Science 13587, Springer 2022, ISBN 978-3-031-17246-5 [contents] - 2021
- [c19]Oguz Kedilioglu, Markus Lieret, Julia Schottenhamml, Tobias Würfl, Andreas Blank, Andreas Maier, Jörg Franke:
RGB-D-based Human Detection and Segmentation for Mobile Robot Navigation in Industrial Environments. VISIGRAPP (4: VISAPP) 2021: 219-226 - [e2]Nandinee Fariah Haq, Patricia Johnson, Andreas Maier, Tobias Würfl, Jaejun Yoo:
Machine Learning for Medical Image Reconstruction - 4th International Workshop, MLMIR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings. Lecture Notes in Computer Science 12964, Springer 2021, ISBN 978-3-030-88551-9 [contents] - 2020
- [b1]Tobias Würfl:
Anwendungen von Datenkonsistenzbedingungen in der Kegelstrahl-Computertomographie (Applications of Data Consistency Conditions in Cone-Beam Computed Tomography). University of Erlangen-Nuremberg, Germany, 2020 - [p1]Andreas Maier, Vincent Christlein, Katharina Breininger, Tobias Würfl, Mathias Unberath, Christian Riess:
Bildanalyse. Handbuch der Künstlichen Intelligenz 2020: 673-712 - [e1]Farah Deeba, Patricia Johnson, Tobias Würfl, Jong Chul Ye:
Machine Learning for Medical Image Reconstruction - Third International Workshop, MLMIR 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings. Lecture Notes in Computer Science 12450, Springer 2020, ISBN 978-3-030-61597-0 [contents] - [i17]Mathis Hoffmann, Claudia Buerhop-Lutz, Luca Reeb, Tobias Pickel, Thilo Winkler, Bernd Doll, Tobias Würfl, Ian Marius Peters, Christoph Brabec, Andreas Maier, Vincent Christlein:
Deep Learning-based Pipeline for Module Power Prediction from EL Measurements. CoRR abs/2009.14712 (2020) - [i16]Lina Felsner, Tobias Würfl, Christopher Syben, Philipp Roser, Alexander Preuhs, Andreas Maier, Christian Riess:
Reconstruction of Voxels with Position- and Angle-Dependent Weightings. CoRR abs/2010.14205 (2020) - [i15]Florian Schiffers, Thomas Bochynek, André Aichert, Tobias Würfl, Michael Rubenstein, Oliver Cossairt:
Disassemblable Fieldwork CT Scanner Using a 3D-printed Calibration Phantom. CoRR abs/2011.06671 (2020) - [i14]Haoyu Wei, Florian Schiffers, Tobias Würfl, Daming Shen, Daniel Kim, Aggelos K. Katsaggelos, Oliver Cossairt:
2-Step Sparse-View CT Reconstruction with a Domain-Specific Perceptual Network. CoRR abs/2012.04743 (2020)
2010 – 2019
- 2019
- [j3]Andreas K. Maier, Christopher Syben, Bernhard Stimpel, Tobias Würfl, Mathis Hoffmann, Frank Schebesch, Weilin Fu, Leonid Mill, Lasse Kling, Silke H. Christiansen:
Learning with known operators reduces maximum error bounds. Nat. Mach. Intell. 1(8): 373-380 (2019) - [c18]Yixing Huang, Tobias Würfl, Katharina Breininger, Ling Liu, Günter Lauritsch, Andreas K. Maier:
Abstract: Some Investigations on Robustness of Deep Learning in Limited Angle Tomography. Bildverarbeitung für die Medizin 2019: 21 - [c17]Christopher Syben, Bernhard Stimpel, Jonathan Lommen, Tobias Würfl, Arnd Dörfler, Andreas K. Maier:
Abstract: Fan-to-Parallel Beam Conversion - Deriving Neural Network Architectures Using Precision Learning. Bildverarbeitung für die Medizin 2019: 29 - [c16]Tobias Würfl, André Aichert, Nicole Maass, Frank Dennerlein, Andreas K. Maier:
Estimating the Fundamental Matrix Without Point Correspondences With Application to Transmission Imaging. ICCV 2019: 1072-1081 - [c15]Bernhard Stimpel, Christopher Syben, Tobias Würfl, Katharina Breininger, Jonathan M. Lommen, Arnd Dörfler, Andreas K. Maier:
Projection image-to-image translation in hybrid x-ray/MR imaging. Image Processing 2019: 109492K - [i13]Andreas K. Maier, Christopher Syben, Bernhard Stimpel, Tobias Würfl, Mathis Hoffmann, Frank Schebesch, Weilin Fu, Leonid Mill, Lasse Kling, Silke H. Christiansen:
Learning with Known Operators reduces Maximum Training Error Bounds. CoRR abs/1907.01992 (2019) - [i12]Tristan Deleu, Tobias Würfl, Mandana Samiei, Joseph Paul Cohen, Yoshua Bengio:
Torchmeta: A Meta-Learning library for PyTorch. CoRR abs/1909.06576 (2019) - [i11]Mandana Samiei, Tobias Würfl, Tristan Deleu, Martin Weiss, Francis Dutil, Thomas Fevens, Geneviève Boucher, Sébastien Lemieux, Joseph Paul Cohen:
The TCGA Meta-Dataset Clinical Benchmark. CoRR abs/1910.08636 (2019) - [i10]Bernhard Stimpel, Christopher Syben, Tobias Würfl, Katharina Breininger, Philip Hoelter, Arnd Dörfler, Andreas K. Maier:
Projection-to-Projection Translation for Hybrid X-ray and Magnetic Resonance Imaging. CoRR abs/1911.08163 (2019) - 2018
- [j2]Tobias Würfl, Mathis Hoffmann, Vincent Christlein, Katharina Breininger, Yixing Huang, Mathias Unberath, Andreas K. Maier:
Deep Learning Computed Tomography: Learning Projection-Domain Weights From Image Domain in Limited Angle Problems. IEEE Trans. Medical Imaging 37(6): 1454-1463 (2018) - [c14]Katharina Breininger, Vincent Christlein, Tobias Würfl, Andreas K. Maier:
Deep Learning Fundamentals. Bildverarbeitung für die Medizin 2018: 5 - [c13]Weilin Fu, Katharina Breininger, Roman Schaffert, Nishant Ravikumar, Tobias Würfl, Jim Fujimoto, Eric Moult, Andreas K. Maier:
Frangi-Net. Bildverarbeitung für die Medizin 2018: 341-346 - [c12]Marc Aubreville, Miguel Goncalves, Christian Knipfer, Nicolai Oetter, Tobias Würfl, Helmut Neumann, Florian Stelzle, Christopher Bohr, Andreas K. Maier:
Patch-based Carcinoma Detection on Confocal Laser Endomicroscopy Images - A Cross-site Robustness Assessment. BIOIMAGING 2018: 27-34 - [c11]Marc Aubreville, Miguel Goncalves, Christian Knipfer, Nicolai Oetter, Tobias Würfl, Helmut Neumann, Florian Stelzle, Christopher Bohr, Andreas K. Maier:
Transferability of Deep Learning Algorithms for Malignancy Detection in Confocal Laser Endomicroscopy Images from Different Anatomical Locations of the Upper Gastrointestinal Tract. BIOSTEC (Selected Papers) 2018: 67-85 - [c10]Christopher Syben, Bernhard Stimpel, Jonathan Lommen, Tobias Würfl, Arnd Dörfler, Andreas Maier:
Deriving Neural Network Architectures Using Precision Learning: Parallel-to-Fan Beam Conversion. GCPR 2018: 503-517 - [c9]Andreas K. Maier, Frank Schebesch, Christopher Syben, Tobias Würfl, Stefan Steidl, Jang Hwan Choi, Rebecca Fahrig:
Precision Learning: Towards Use of Known Operators in Neural Networks. ICPR 2018: 183-188 - [c8]Katharina Breininger, Tobias Würfl, Tanja Kurzendorfer, Shadi Albarqouni, Marcus Pfister, Markus Kowarschik, Nassir Navab, Andreas K. Maier:
Multiple Device Segmentation for Fluoroscopic Imaging Using Multi-task Learning. CVII-STENT/LABELS@MICCAI 2018: 19-27 - [c7]Felix Horger, Tobias Würfl, Vincent Christlein, Andreas K. Maier:
Towards Arbitrary Noise Augmentation - Deep Learning for Sampling from Arbitrary Probability Distributions. MLMIR@MICCAI 2018: 129-137 - [c6]Yixing Huang, Tobias Würfl, Katharina Breininger, Ling Liu, Günter Lauritsch, Andreas K. Maier:
Some Investigations on Robustness of Deep Learning in Limited Angle Tomography. MICCAI (1) 2018: 145-153 - [c5]Maximilian Seitzer, Guang Yang, Jo Schlemper, Ozan Oktay, Tobias Würfl, Vincent Christlein, Tom Wong, Raad Mohiaddin, David N. Firmin, Jennifer Keegan, Daniel Rueckert, Andreas K. Maier:
Adversarial and Perceptual Refinement for Compressed Sensing MRI Reconstruction. MICCAI (1) 2018: 232-240 - [i9]Felix Horger, Tobias Würfl, Vincent Christlein, Andreas K. Maier:
Deep Learning for Sampling from Arbitrary Probability Distributions. CoRR abs/1801.04211 (2018) - [i8]Bernhard Stimpel, Christopher Syben, Tobias Würfl, Katharina Breininger, Katrin Mentl, Jonathan Lommen, Arnd Dörfler, Andreas K. Maier:
Projection image-to-image translation in hybrid X-ray/MR imaging. CoRR abs/1804.03955 (2018) - [i7]Maximilian Seitzer, Guang Yang, Jo Schlemper, Ozan Oktay, Tobias Würfl, Vincent Christlein, Tom Wong, Raad Mohiaddin, David N. Firmin, Jennifer Keegan, Daniel Rueckert, Andreas K. Maier:
Adversarial and Perceptual Refinement for Compressed Sensing MRI Reconstruction. CoRR abs/1806.11216 (2018) - [i6]Christopher Syben, Bernhard Stimpel, Jonathan Lommen, Tobias Würfl, Arnd Dörfler, Andreas K. Maier:
Deriving Neural Network Architectures using Precision Learning: Parallel-to-fan beam Conversion. CoRR abs/1807.03057 (2018) - 2017
- [c4]Vincent Christlein, Florin C. Ghesu, Tobias Würfl, Andreas K. Maier, Fabian Isensee, Peter Neher, Klaus H. Maier-Hein:
Tutorial: Deep Learning Advancing the State-of-the-Art in Medical Image Analysis. Bildverarbeitung für die Medizin 2017: 6-7 - [c3]Kerstin Hammernik, Tobias Würfl, Thomas Pock, Andreas K. Maier:
A Deep Learning Architecture for Limited-Angle Computed Tomography Reconstruction. Bildverarbeitung für die Medizin 2017: 92-97 - [c2]Elisabeth Hoppe, Gregor Körzdörfer, Tobias Würfl, Jens Wetzl, Felix Lugauer, Josef Pfeuffer, Andreas K. Maier:
Deep Learning for Magnetic Resonance Fingerprinting: A New Approach for Predicting Quantitative Parameter Values from Time Series. GMDS 2017: 202-206 - [i5]Marc Aubreville, Miguel Goncalves, Christian Knipfer, Nicolai Oetter, Tobias Würfl, Helmut Neumann, Florian Stelzle, Christopher Bohr, Andreas K. Maier:
Patch-based Carcinoma Detection on Confocal Laser Endomicroscopy Images - A Cross-Site Robustness Assessment. CoRR abs/1707.08149 (2017) - [i4]Christopher Syben, Bernhard Stimpel, Katharina Breininger, Tobias Würfl, Rebecca Fahrig, Arnd Dörfler, Andreas K. Maier:
A Deep Learning Approach for Reconstruction Filter Kernel Discretization. CoRR abs/1710.06287 (2017) - [i3]Bernhard Stimpel, Christopher Syben, Tobias Würfl, Katrin Mentl, Arnd Dörfler, Andreas K. Maier:
MR to X-Ray Projection Image Synthesis. CoRR abs/1710.07498 (2017) - [i2]Weilin Fu, Katharina Breininger, Tobias Würfl, Nishant Ravikumar, Roman Schaffert, Andreas K. Maier:
Frangi-Net: A Neural Network Approach to Vessel Segmentation. CoRR abs/1711.03345 (2017) - [i1]Andreas K. Maier, Frank Schebesch, Christopher Syben, Tobias Würfl, Stefan Steidl, Jang Hwan Choi, Rebecca Fahrig:
Precision Learning: Towards Use of Known Operators in Neural Networks. CoRR abs/1712.00374 (2017) - 2016
- [j1]Martin Sedlmayr, Tobias Würfl, Christian Maier, Lothar Häberle, Peter A. Fasching, Hans-Ulrich Prokosch, Jan Christoph:
Optimizing R with SparkR on a commodity cluster for biomedical research. Comput. Methods Programs Biomed. 137: 321-328 (2016) - [c1]Tobias Würfl, Florin C. Ghesu, Vincent Christlein, Andreas K. Maier:
Deep Learning Computed Tomography. MICCAI (3) 2016: 432-440
Coauthor Index
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