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Multimodal 3D medical image registration guided by shape encoder–decoder networks
International Journal of Computer Assisted Radiology and Surgery, 15, 269-276, 2020
Deep Multi-Modal Encoder-Decoder Networks for Shape Constrained Segmentation and Joint Representation Learning
In: (eds.), Bildverarbeitung für die Medizin 2019, Lübeck, Informatik aktuell, Springer Vieweg, Wiesbaden, 23-28, 2019
Model-Based 4D Segmentation of Cardiac Structures in Cine MRI Sequences
In: (eds.), Bildverarbeitung für die Medizin 2017, Heidelberg, Informatik aktuell, Springer Vieweg, Berlin Heidelberg, 18-23, 2017
Deep 3D Encoder-Decoder Networks with Applications to Organ Segmentation
In: (eds.), Student Conference 2018, Medical Engineering Science, Medical Informatics and Biomediacal Engineering, Lübeck, Infinite Science Publishing, 229-232, 2018
OBELISK-Net: Fewer layers to solve 3D multi-organ segmentation with sparse deformable convolutions
Medical Image Analysis, 54, 1-9, 2019
OBELISK – One Kernel to Solve Nearly Everything:Unified 3D Binary Convolutions for Image Analysis
In: Conference on Medical Imaging with Deep Learning (MIDL 2018), 2018
Learning to Predict Ischemic Stroke Growth on Acute CT Perfusion Data by Interpolating Low-Dimensional Shape Representations
Frontiers in Neurology, 9, 989, 2018
English
DeutschMedizinische Informatik
an der Uni Lübeck studieren
Institutssekretariat
Susanne Petersen
Tel+49 451 3101 5601
Fax+49 451 3101 5604
Gebäude 64 (Informatik)
Ratzeburger Allee 160
23538 Lübeck
Deutschland
Susanne Petersen
Tel+49 451 3101 5601
Fax+49 451 3101 5604
Gebäude 64 (Informatik)
Ratzeburger Allee 160
23538 Lübeck
Deutschland