Lasse Hansen
Lasse Hansen
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Zitiert von
Zitiert von
Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning
A Hering, L Hansen, TCW Mok, ACS Chung, H Siebert, S Häger, A Lange, ...
IEEE Transactions on Medical Imaging 42 (3), 697-712, 2022
CrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation
R Dorent, A Kujawa, M Ivory, S Bakas, N Rieke, S Joutard, B Glocker, ...
Medical Image Analysis 83, 102628, 2023
GraphRegNet: Deep graph regularisation networks on sparse keypoints for dense registration of 3D lung CTs
L Hansen, MP Heinrich
IEEE Transactions on Medical Imaging 40 (9), 2246-2257, 2021
Highly accurate and memory efficient unsupervised learning-based discrete CT registration using 2.5 D displacement search
MP Heinrich, L Hansen
International Conference on Medical Image Computing and Computer-Assisted …, 2020
Weakly-supervised learning of multi-modal features for regularised iterative descent in 3D image registration
M Blendowski, L Hansen, MP Heinrich
Medical image analysis 67, 101822, 2021
Fast 3D registration with accurate optimisation and little learning for Learn2Reg 2021
H Siebert, L Hansen, MP Heinrich
International Conference on Medical Image Computing and Computer-Assisted …, 2021
Biomedical image analysis competitions: The state of current participation practice
M Eisenmann, A Reinke, V Weru, MD Tizabi, F Isensee, TJ Adler, ...
arXiv preprint arXiv:2212.08568, 2022
Fusing information from multiple 2D depth cameras for 3D human pose estimation in the operating room
L Hansen, M Siebert, J Diesel, MP Heinrich
International journal of computer assisted radiology and surgery 14, 1871-1879, 2019
Why is the winner the best?
M Eisenmann, A Reinke, V Weru, MD Tizabi, F Isensee, TJ Adler, S Ali, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
Deep learning based geometric registration for medical images: How accurate can we get without visual features?
L Hansen, MP Heinrich
Information Processing in Medical Imaging: 27th International Conference …, 2021
Learning deformable point set registration with regularized dynamic graph cnns for large lung motion in copd patients
L Hansen, D Dittmer, MP Heinrich
Graph Learning in Medical Imaging: First International Workshop, GLMI 2019 …, 2019
Voxelmorph++ going beyond the cranial vault with keypoint supervision and multi-channel instance optimisation
MP Heinrich, L Hansen
International Workshop on Biomedical Image Registration, 85-95, 2022
Tackling the problem of large deformations in deep learning based medical image registration using displacement embeddings
L Hansen, MP Heinrich
arXiv preprint arXiv:2005.13338, 2020
7dof hand and arm tracking for teleoperation of anthropomorphic robots
J Grasshoff, L Hansen, I Kuhlemann, K Ehlers
Proceedings of ISR 2016: 47st International Symposium on Robotics, 1-8, 2016
Anatomy-guided domain adaptation for 3D in-bed human pose estimation
A Bigalke, L Hansen, J Diesel, C Hennigs, P Rostalski, MP Heinrich
Medical Image Analysis 89, 102887, 2023
Adapting the mean teacher for keypoint-based lung registration under geometric domain shifts
A Bigalke, L Hansen, MP Heinrich
International Conference on Medical Image Computing and Computer-Assisted …, 2022
Geometric deep learning and heatmap prediction for large deformation registration of abdominal and thoracic CT
IY Ha, L Hansen, M Wilms, MP Heinrich
Learning a metric for multimodal medical image registration without supervision based on cycle constraints
H Siebert, L Hansen, MP Heinrich
Sensors 22 (3), 1107, 2022
Revisiting iterative highly efficient optimisation schemes in medical image registration
L Hansen, MP Heinrich
Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021
Radiographic Assessment of CVC Malpositioning: How can AI best support clinicians?
L Hansen, M Sieren, M Hobe, A Saalbach, H Schulz, J Barkhausen, ...
Medical imaging with deep learning, 2021
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