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2020 – today
- 2021
[j4]Max Blendowski, Lasse Hansen, Mattias P. Heinrich
:
Weakly-supervised learning of multi-modal features for regularised iterative descent in 3D image registration. Medical Image Anal. 67: 101822 (2021)- 2020
- [j3]Max Blendowski, Nassim Bouteldja, Mattias P. Heinrich:
Multimodal 3D medical image registration guided by shape encoder-decoder networks. Int. J. Comput. Assist. Radiol. Surg. 15(2): 269-276 (2020) - [c10]Lasse Hansen, Maximilian Blendowski, Mattias P. Heinrich:
Abstract: Defence of Mathematical Models for Deep Learning based Registration. Bildverarbeitung für die Medizin 2020: 32 - [c9]Maximilian Blendowski, Mattias P. Heinrich:
Abstract: Self-Supervised 3D Context Feature Learning on Unlabeled Volume Data. Bildverarbeitung für die Medizin 2020: 192 - [i2]Max Blendowski, Mattias P. Heinrich:
Learning to map between ferns with differentiable binary embedding networks. CoRR abs/2005.12563 (2020)
2010 – 2019
- 2019
- [j2]Max Blendowski, Mattias P. Heinrich:
Combining MRF-based deformable registration and deep binary 3D-CNN descriptors for large lung motion estimation in COPD patients. Int. J. Comput. Assist. Radiol. Surg. 14(1): 43-52 (2019) - [c8]Maximilian Blendowski, Hannes Nickisch, Mattias P. Heinrich:
How to Learn from Unlabeled Volume Data: Self-supervised 3D Context Feature Learning. MICCAI (6) 2019: 649-657 - [c7]Max Blendowski, Mattias P. Heinrich:
Learning interpretable multi-modal features for alignment with supervised iterative descent. MIDL 2019: 73-83 - 2018
- [j1]Mattias P. Heinrich, Max Blendowski, Ozan Oktay:
TernaryNet: faster deep model inference without GPUs for medical 3D segmentation using sparse and binary convolutions. Int. J. Comput. Assist. Radiol. Surg. 13(9): 1311-1320 (2018) - [c6]Max Blendowski, Mattias P. Heinrich:
3D-CNNs for Deep Binary Descriptor Learning in Medical Volume Data. Bildverarbeitung für die Medizin 2018: 23-28 - [i1]Mattias P. Heinrich, Maximilian Blendowski, Ozan Oktay:
TernaryNet: Faster Deep Model Inference without GPUs for Medical 3D Segmentation using Sparse and Binary Convolutions. CoRR abs/1801.09449 (2018) - 2017
- [c5]Maximilian Blendowski, Mattias P. Heinrich:
Abstract: Kombination binärer Kontextfeatures mit Vantage Point Forests zur Multi-Organ-Segmentierung. Bildverarbeitung für die Medizin 2017: 24 - 2016
- [c4]Mattias P. Heinrich, Maximilian Blendowski:
Multi-organ Segmentation Using Vantage Point Forests and Binary Context Features. MICCAI (2) 2016: 598-606 - 2013
- [c3]Maximilian Blendowski, Matthias Wilms, René Werner, Heinz Handels:
Simulation und Evaluation tiefenbildgebender Verfahren zur Prädiktion atmungsbedingter Organ- und Tumorbewegungen. Bildverarbeitung für die Medizin 2013: 350-355 - [c2]Matthias Wilms, René Werner, Jan Ehrhardt, Alexander Schmidt-Richberg, Maximilian Blendowski, Heinz Handels:
Surrogate-based diffeomorphic motion estimation for radiation therapy: comparison of multivariate regression approaches. Image Processing 2013: 866915 - 2012
- [c1]René Werner, Jan Ehrhardt, Alexander Schmidt-Richberg, Matthias Wilms, Maximilian Blendowski, Heinz Handels:
A Diffeomorphic Framework for Surrogate-based Motion Estimation in Radiation Therapy: Concept and First Evaluation. GI-Jahrestagung 2012: 1774-1785
Coauthor Index
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