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End-to-end learning of body weight prediction from point clouds with basis point sets
In: (eds.), Bildverarbeitung für die Medizin 2021, Regensburg, Informatik aktuell, Springer Vieweg, Wiesbaden, 254-259, 2021
Weakly-supervised learning of multi-modal features for regularised iterative descent in 3D image registration
Medical Image Analysis, 67, 101822, 2021
Probabilistic Dense Displacement Networks for Medical Image Registration - Contributions to the Learn2Reg challenge
In: (eds.), Bildverarbeitung für die Medizin 2021, Regensburg, Informatik aktuell, Springer Vieweg, Wiesbaden, 125-126, 2021
Multi-modal Unsupervised Domain Adaptation for Deformable Registration Based on Maximum Classifier Discrepancy
In: (eds.), Bildverarbeitung für die Medizin 2021, Regensburg, Informatik aktuell, Springer Vieweg, Wiesbaden, 192-197, 2021
Evaluating Design Choices for Deep Learning Registration Networks - Architecture Matters
In: (eds.), Bildverarbeitung für die Medizin 2021, Regensburg, Informatik aktuell, Springer Vieweg, Wiesbaden, 111-116, 2021
Fast Pulmonary Fissure Detection in CT Scans using Deep Learning on Point Clouds
In: (eds.), Student Conference 2020, Medical Engineering Science, Medical Informatics, Biomedical Engineering and Auditory Technology, Lübeck, Infinite Science Publishing, 201-204, 2020
Defence of Mathematical Models for Deep Learning based Registration
In: (eds.), Bildverarbeitung für die Medizin 2020, Berlin, Informatik aktuell, Springer Vieweg, Wiesbaden, 32, 2020
Highly Accurate and Memory Efficient Unsupervised Learning-Based Discrete CT Registration Using 2.5D Displacement Search
In: Medical Image Computing and Computer Assisted Intervention – MICCAI 2020, Cham, Springer, 12263, 190-200, 2020
Unsupervised learning of multimodal image registration using domain adaptation with projected Earth Mover’s discrepancies
In: International Conference on Medical Imaging with Deep Learning, 2020
Der Einfluss von Segmentierung auf die Genauigkeit eines CNN-Klassifikators zur Mimik-Steuerung
In: (eds.), Bildverarbeitung für die Medizin 2020, Berlin, Informatik aktuell, Springer Vieweg, Wiesbaden, 294-300, 2020
Deep Learning for Prediction of Diaphragm Activity from the Surface Electromyogram
Current Directions in Biomedical Engineering, 5, 1, 17-20, 2019
Fusing information from multiple 2D depth cameras for 3D human pose estimation in the operating room
International Journal of Computer Assisted Radiology and Surgery, 14, 11, 1871-1879, 2019
Learning Deformable Point Set Registration with Regularized Dynamic Graph CNNs for Large Lung Motion in COPD Patients
In: Graph Learning in Medical Imaging. GLMI 2019, Cham, Lecture Notes in Computer Science, Springer, 11849, 53-61, 2019
Multi-Kernel Diffusion CNNs for Graph-Based Learning on Point Clouds
In: Computer Vision – ECCV 2018 Workshops, Cham, Lecture Notes in Computer Science, Springer, 11131, 4413, 456-469, 2019
Regularized Landmark Detection with CAEs for Human Pose Estimation in the Operating Room
In: (eds.), Bildverarbeitung für die Medizin 2019, Lübeck, Informatik aktuell, Springer Vieweg, Wiesbaden, 178-183, 2019
Sparse Structured Prediction for Semantic Edge Detection in Medical Images
In: International Conference on Medical Imaging with Deep Learning, PMLR, 102, 250-259, 2019
Human Pose Estimation with Hourglass Network and Convolutional Autoencoder
In: (eds.), Student Conference 2019, Medical Engineering Science, Medical Informatics, Biomedical Engineering and Auditory Technology, Lübeck, Infinite Science Publishing, 141-144, 2019
Transferring a Deep Cityscape Synthesis Approach to the Medical Domain
In: (eds.), Student Conference 2018, Medical Engineering Science, Medical Informatics and Biomediacal Engineering, Lübeck, Infinite Science Publishing, 91-94, 2018
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Susanne Petersen
Tel+49 451 3101 5601
Fax+49 451 3101 5604
Ratzeburger Allee 160
23538 Lübeck
Germany