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Maximilian Schulze-Hagen
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2020 – today
- 2024
- [j3]Daniel Truhn, Soroosh Tayebi Arasteh, Oliver Lester Saldanha, Gustav Müller-Franzes, Firas Khader, Philip Quirke, Nicholas P. West, Richard Gray, Gordon G. A. Hutchins, Jacqueline A. James, Maurice B. Loughrey, Manuel Salto-Tellez, Hermann Brenner, Alexander Brobeil, Tanwei Yuan, Jenny Chang-Claude, Michael Hoffmeister, Sebastian Foersch, Tianyu Han, Sebastian Keil, Maximilian Schulze-Hagen, Peter Isfort, Philipp Bruners, Georgios Kaissis, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather:
Encrypted federated learning for secure decentralized collaboration in cancer image analysis. Medical Image Anal. 92: 103059 (2024) - 2022
- [j2]Felix Duong, Michael Gadermayr, Dorit Merhof, Christiane Kuhl, Philipp Bruners, Sven H. Loosen, Christoph Roderburg, Daniel Truhn, Maximilian F. Schulze-Hagen:
Automated major psoas muscle volumetry in computed tomography using machine learning algorithms. Int. J. Comput. Assist. Radiol. Surg. 17(2): 355-361 (2022) - [j1]Tianyu Han, Jakob Nikolas Kather, Federico Pedersoli, Markus Zimmermann, Sebastian Keil, Maximilian Schulze-Hagen, Marc Terwoelbeck, Peter Isfort, Christoph Haarburger, Fabian Kiessling, Christiane Kuhl, Volkmar Schulz, Sven Nebelung, Daniel Truhn:
Image prediction of disease progression for osteoarthritis by style-based manifold extrapolation. Nat. Mac. Intell. 4(11): 1029-1039 (2022) - [i3]Firas Khader, Gustav Mueller-Franzes, Soroosh Tayebi Arasteh, Tianyu Han, Christoph Haarburger, Maximilian Schulze-Hagen, Philipp Schad, Sandy Engelhardt, Bettina Baeßler, Sebastian Foersch, Johannes Stegmaier, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather, Daniel Truhn:
Medical Diffusion - Denoising Diffusion Probabilistic Models for 3D Medical Image Generation. CoRR abs/2211.03364 (2022) - 2021
- [i2]Tianyu Han, Jakob Nikolas Kather, Federico Pedersoli, Markus Zimmermann, Sebastian Keil, Maximilian Schulze-Hagen, Marc Terwoelbeck, Peter Isfort, Christoph Haarburger, Fabian Kiessling, Volkmar Schulz, Christiane Kuhl, Sven Nebelung, Daniel Truhn:
Predicting Osteoarthritis Progression in Radiographs via Unsupervised Representation Learning. CoRR abs/2111.11439 (2021) - 2020
- [c1]Marcin Kopaczka, Richard Lindenpütz, Daniel Truhn, Maximilian Schulze-Hagen, Dorit Merhof:
Fully Automated Segmentation of the Psoas Major Muscle in Clinical CT Scans. Bildverarbeitung für die Medizin 2020: 55-60 - [i1]Tianyu Han, Sven Nebelung, Federico Pedersoli, Markus Zimmermann, Maximilian Schulze-Hagen, Michael Ho, Christoph Haarburger, Fabian Kiessling, Christiane Kuhl, Volkmar Schulz, Daniel Truhn:
Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalization. CoRR abs/2011.13011 (2020)
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