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Mattias P Heinrich

Showing results (1-10 of 51) with videos related to

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International Journal of Computer Assisted Radiology and Surgery|November 16, 2018
Combining MRF-based deformable registration and deep binary 3D-CNN descriptors for large lung motion estimation in COPD patientsMax Blendowski, Mattias P Heinrich
IEEE Transactions on Medical Imaging|April 19, 2021
GraphRegNet: Deep Graph Regularisation Networks on Sparse Keypoints for Dense Registration of 3D Lung CTsLasse Hansen, Mattias P Heinrich
Computer Methods and Programs in Biomedicine|October 3, 2021
Modality-agnostic self-supervised deep feature learning and fast instance optimisation for multimodal fusion in ultrasound-guided interventionsIn Young Ha, Mattias P Heinrich
International Journal of Computer Assisted Radiology and Surgery|November 20, 2019
Multimodal 3D medical image registration guided by shape encoder-decoder networksMax Blendowski, Nassim Bouteldja, Mattias P Heinrich
Medical Image Analysis|November 9, 2020
Weakly-supervised learning of multi-modal features for regularised iterative descent in 3D image registrationMax Blendowski, Lasse Hansen, Mattias P Heinrich
Medical Image Analysis|February 27, 2019
OBELISK-Net: Fewer layers to solve 3D multi-organ segmentation with sparse deformable convolutionsMattias P Heinrich, Ozan Oktay, Nassim Bouteldja
International Journal of Computer Assisted Radiology and Surgery|June 1, 2018
TernaryNet: faster deep model inference without GPUs for medical 3D segmentation using sparse and binary convolutionsMattias P Heinrich, Max Blendowski, Ozan Oktay
Sensors (Basel, Switzerland)|February 15, 2022
Learning a Metric for Multimodal Medical Image Registration without Supervision Based on Cycle ConstraintsHanna Siebert, Lasse Hansen, Mattias P Heinrich
Journal of Biomedical Informatics|May 22, 2021
Dynamic deformable attention network (DDANet) for COVID-19 lesions semantic segmentationKumar T Rajamani, Hanna Siebert, Mattias P Heinrich
International Journal of Computer Assisted Radiology and Surgery|September 21, 2019
Memory-efficient 2.5D convolutional transformer networks for multi-modal deformable registration with weak label supervision applied to whole-heart CT and MRI scansAlessa Hering, Sven Kuckertz, Stefan Heldmann, et al.
Pageof 6

Showing results (1-10 of 51) with videos related to

Sort By:
Pageof 6
International Journal of Computer Assisted Radiology and Surgery|November 16, 2018
Combining MRF-based deformable registration and deep binary 3D-CNN descriptors for large lung motion estimation in COPD patientsMax Blendowski, Mattias P Heinrich
IEEE Transactions on Medical Imaging|April 19, 2021
GraphRegNet: Deep Graph Regularisation Networks on Sparse Keypoints for Dense Registration of 3D Lung CTsLasse Hansen, Mattias P Heinrich
Computer Methods and Programs in Biomedicine|October 3, 2021
Modality-agnostic self-supervised deep feature learning and fast instance optimisation for multimodal fusion in ultrasound-guided interventionsIn Young Ha, Mattias P Heinrich
International Journal of Computer Assisted Radiology and Surgery|November 20, 2019
Multimodal 3D medical image registration guided by shape encoder-decoder networksMax Blendowski, Nassim Bouteldja, Mattias P Heinrich
Medical Image Analysis|November 9, 2020
Weakly-supervised learning of multi-modal features for regularised iterative descent in 3D image registrationMax Blendowski, Lasse Hansen, Mattias P Heinrich
Medical Image Analysis|February 27, 2019
OBELISK-Net: Fewer layers to solve 3D multi-organ segmentation with sparse deformable convolutionsMattias P Heinrich, Ozan Oktay, Nassim Bouteldja
International Journal of Computer Assisted Radiology and Surgery|June 1, 2018
TernaryNet: faster deep model inference without GPUs for medical 3D segmentation using sparse and binary convolutionsMattias P Heinrich, Max Blendowski, Ozan Oktay
Sensors (Basel, Switzerland)|February 15, 2022
Learning a Metric for Multimodal Medical Image Registration without Supervision Based on Cycle ConstraintsHanna Siebert, Lasse Hansen, Mattias P Heinrich
Journal of Biomedical Informatics|May 22, 2021
Dynamic deformable attention network (DDANet) for COVID-19 lesions semantic segmentationKumar T Rajamani, Hanna Siebert, Mattias P Heinrich
International Journal of Computer Assisted Radiology and Surgery|September 21, 2019
Memory-efficient 2.5D convolutional transformer networks for multi-modal deformable registration with weak label supervision applied to whole-heart CT and MRI scansAlessa Hering, Sven Kuckertz, Stefan Heldmann, et al.
Pageof 6