Recreating Riser Slugging Flow Based on an Economic Lab-Sized Setup. - Lasse Hansen; Simon Pedersen; Zhenyu Yang 001; Jakob Biltoft (PSYCO, 2013)

Autonomous optimization of fine motions for robotic assembly. - Emil Krabbe; Ewa Kristiansen; Lasse Hansen; David A. Bourne (ICRA, 2014)

Multi-kernel Diffusion CNNs for Graph-Based Learning on Point Clouds. - Lasse Hansen; Jasper Diesel; Mattias P. Heinrich (ECCV Workshops (3), 2018)

Regularized Landmark Detection with CAEs for Human Pose Estimation in the Operating Room. - Lasse Hansen; Jasper Diesel; Mattias P. Heinrich (Bildverarbeitung für die Medizin, 2019)

Learning Deformable Point Set Registration with Regularized Dynamic Graph CNNs for Large Lung Motion in COPD Patients. - Lasse Hansen; Doris Dittmer; Mattias P. Heinrich (GLMI@MICCAI, 2019)

Sparse Structured Prediction for Semantic Edge Detection in Medical Images. - Lasse Hansen; Mattias P. Heinrich (MIDL, 2019)

Fusing information from multiple 2D depth cameras for 3D human pose estimation in the operating room. - Lasse Hansen; Marlin Siebert; Jasper Diesel; Mattias P. Heinrich (Int. J. Comput. Assist. Radiol. Surg., 2019)

Abstract: Defence of Mathematical Models for Deep Learning based Registration. - Lasse Hansen; Maximilian Blendowski; Mattias P. Heinrich (Bildverarbeitung für die Medizin, 2020)

Der Einfluss von Segmentierung auf die Genauigkeit eines CNN-Klassifikators zur Mimik-Steuerung. - Ron Keuth; Lasse Hansen; Mattias P. Heinrich (Bildverarbeitung für die Medizin, 2020)

Discrete Unsupervised 3D Registration Methods for the Learn2Reg Challenge. - Lasse Hansen; Mattias P. Heinrich (MICCAI (Challenges), 2020)

Highly Accurate and Memory Efficient Unsupervised Learning-Based Discrete CT Registration Using 2.5D Displacement Search. - Mattias P. Heinrich; Lasse Hansen (MICCAI (3), 2020)

Tackling the Problem of Large Deformations in Deep Learning Based Medical Image Registration Using Displacement Embeddings. - Lasse Hansen; Mattias P. Heinrich (CoRR, 2020)

Unsupervised learning of multimodal image registration using domain adaptation with projected Earth Move's discrepancies. - Mattias P. Heinrich; Lasse Hansen (CoRR, 2020)

A Novel Strategy for Automatic Error Classification and Error Recovery for Robotic Assembly in Flexible Production. - Ewa Kristiansen; Emil Krabbe Nielsen; Lasse Hansen; David A. Bourne (J. Intell. Robotic Syst., 2020)

End-to-end Learning of Body Weight Prediction from Point Clouds with Basis Point Sets. - Alexander Bigalke; Lasse Hansen; Mattias P. Heinrich (Bildverarbeitung für die Medizin, 2021)

Abstract: Probabilistic Dense Displacement Networks for Medical Image Registration - Contributions to the Learn2Reg Challenge. - Lasse Hansen; Mattias P. Heinrich (Bildverarbeitung für die Medizin, 2021)

Multi-modal Unsupervised Domain Adaptation for Deformable Registration Based on Maximum Classifier Discrepancy. - Christian N. Kruse; Lasse Hansen; Mattias P. Heinrich (Bildverarbeitung für die Medizin, 2021)

Evaluating Design Choices for Deep Learning Registration Networks - Architecture Matters. - Hanna Siebert; Lasse Hansen; Mattias P. Heinrich (Bildverarbeitung für die Medizin, 2021)

DaCy: A Unified Framework for Danish NLP. - Kenneth C. Enevoldsen; Lasse Hansen; Kristoffer L. Nielbo (CHR, 2021)

Deep Learning Based Geometric Registration for Medical Images: How Accurate Can We Get Without Visual Features? - Lasse Hansen; Mattias P. Heinrich (IPMI, 2021)

Revisiting Iterative Highly Efficient Optimisation Schemes in Medical Image Registration. - Lasse Hansen; Mattias P. Heinrich (MICCAI (4), 2021)

Fast 3D Registration with Accurate Optimisation and Little Learning for Learn2Reg 2021. - Hanna Siebert; Lasse Hansen; Mattias P. Heinrich (MIDOG/MOOD/Learn2Reg@MICCAI, 2021)

Seeing under the cover with a 3D U-Net: point cloud-based weight estimation of covered patients. - Alexander Bigalke; Lasse Hansen; Jasper Diesel; Mattias P. Heinrich (Int. J. Comput. Assist. Radiol. Surg., 2021)

Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning. - Alessa Hering; Lasse Hansen; Tony C. W. Mok; Albert C. S. Chung; Hanna Siebert; Stephanie Häger; Annkristin Lange; Sven Kuckertz; Stefan Heldmann; Wei Shao 008; Sulaiman Vesal; Mirabela Rusu; et al. (CoRR, 2021)

Weakly-supervised learning of multi-modal features for regularised iterative descent in 3D image registration. - Max Blendowski; Lasse Hansen; Mattias P. Heinrich (Medical Image Anal., 2021)

GraphRegNet: Deep Graph Regularisation Networks on Sparse Keypoints for Dense Registration of 3D Lung CTs. - Lasse Hansen; Mattias P. Heinrich (IEEE Trans. Medical Imaging, 2021)

Learning an Airway Atlas from Lung CT Using Semantic Inter-patient Deformable Registration. - Fenja Falta; Lasse Hansen; Marian Himstedt; Mattias P. Heinrich (Bildverarbeitung für die Medizin, 2022)

Spatiotemporal Attention for Realtime Segmentation of Corrupted Sequential Ultrasound Data - Improving Usability of AI-based Image Guidance. - Laura Graf 001; Sven Mischkewitz; Lasse Hansen; Mattias P. Heinrich (Bildverarbeitung für die Medizin, 2022)

Support Point Sets for Improving Contactless Interaction in Geometric Learning for Hand Pose Estimation. - Niklas Hermes; Lasse Hansen; Alexander Bigalke; Mattias P. Heinrich (Bildverarbeitung für die Medizin, 2022)

Employing ConvexAdam for BraTS-Reg. - Christoph Großbröhmer; Hanna Siebert; Lasse Hansen; Mattias P. Heinrich (BrainLes@MICCAI, 2022)

XEdgeConv: Leveraging graph convolutions for efficient, permutation- and rotation-invariant dense 3D medical image segmentation. - Christian Weihsbach; Lasse Hansen; Mattias P. Heinrich (GeoMedIA, 2022)

Adapting the Mean Teacher for Keypoint-Based Lung Registration Under Geometric Domain Shifts. - Alexander Bigalke; Lasse Hansen; Mattias P. Heinrich (MICCAI (6), 2022)

Learning Iterative Optimisation for Deformable Image Registration of Lung CT with Recurrent Convolutional Networks. - Fenja Falta; Lasse Hansen; Mattias P. Heinrich (MICCAI (6), 2022)

Domain adaptation through anatomical constraints for 3d human pose estimation under the cover. - Alexander Bigalke; Lasse Hansen; Jasper Diesel; Mattias P. Heinrich (MIDL, 2022)

Voxelmorph++ - Going Beyond the Cranial Vault with Keypoint Supervision and Multi-channel Instance Optimisation. - Mattias P. Heinrich; Lasse Hansen (WBIR, 2022)

CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwnannoma and Cochlea Segmentation. - Reuben Dorent; Aaron Kujawa; Marina Ivory; Spyridon Bakas; Nicola Rieke; Samuel Joutard; Ben Glocker; Jorge Cardoso 002; Marc Modat; Kayhan Batmanghelich; Arseniy Belkov; Maria G. Baldeon Calisto; et al. (CoRR, 2022)

Biomedical image analysis competitions: The state of current participation practice. - Matthias Eisenmann; Annika Reinke; Vivienn Weru; Minu Dietlinde Tizabi; Fabian Isensee; Tim J. Adler; Patrick Godau; Veronika Cheplygina; Michal Kozubek 001; Sharib Ali; Anubha Gupta; Jan Kybic; et al. (CoRR, 2022)

Learning a Metric for Multimodal Medical Image Registration without Supervision Based on Cycle Constraints. - Hanna Siebert; Lasse Hansen; Mattias P. Heinrich (Sensors, 2022)

Why is the Winner the Best? - Matthias Eisenmann; Annika Reinke; Vivienn Weru; Minu Dietlinde Tizabi; Fabian Isensee; Tim J. Adler; Sharib Ali; Vincent Andrearczyk; Marc Aubreville; Ujjwal Baid; Spyridon Bakas; Niranjan Balu; et al. (CVPR, 2023)

Chasing clouds: Differentiable volumetric rasterisation of point clouds as a highly efficient and accurate loss for large-scale deformable 3D registration. - Mattias P. Heinrich; Alexander Bigalke; Christoph Großbröhmer; Lasse Hansen (ICCV, 2023)

Unsupervised 3D Registration Through Optimization-Guided Cyclical Self-training. - Alexander Bigalke; Lasse Hansen; Tony C. W. Mok; Mattias P. Heinrich (MICCAI (10), 2023)

Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark. - Lasse Hansen; Nabeel Seedat; Mihaela van der Schaar; Andrija Petrovic (NeurIPS, 2023)

TextDescriptives: A Python package for calculating a large variety of statistics from text. - Lasse Hansen; Kenneth C. Enevoldsen (CoRR, 2023)

Automated speech- and text-based classification of neuropsychiatric conditions in a multidiagnostic setting. - Lasse Hansen; Roberta Rocca; Arndis Simonsen; Alberto Parola; Vibeke Bliksted; Nicolai Ladegaard; Dan Bang; Kristian Tylén; Ethan Weed; Søren Dinesen Østergaard; Riccardo Fusaroli (CoRR, 2023)

Why is the winner the best? - Matthias Eisenmann; Annika Reinke; Vivienn Weru; Minu Dietlinde Tizabi; Fabian Isensee; Tim J. Adler; Sharib Ali; Vincent Andrearczyk; Marc Aubreville; Ujjwal Baid; Spyridon Bakas; Niranjan Balu; et al. (CoRR, 2023)

Danish Foundation Models. - Kenneth C. Enevoldsen; Lasse Hansen; Dan S. Nielsen; Rasmus A. F. Egebæk; Søren V. Holm; Martin Carsten Nielsen; Martin Bernstorff; Rasmus Larsen 001; Peter B. Jørgensen; Malte Højmark-Bertelsen; Peter Bjerregaard Vahlstrup; Per Møldrup-Dalum; et al. (CoRR, 2023)

CrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation. - Reuben Dorent; Aaron Kujawa; Marina Ivory; Spyridon Bakas; Nicola Rieke; Samuel Joutard; Ben Glocker; M. Jorge Cardoso; Marc Modat; Kayhan Batmanghelich; Arseniy Belkov; Maria G. Baldeon Calisto; et al. (Medical Image Anal., 2023)

Point clouds and keypoint graphs in 3D deep learning for medical image analysis. - Lasse Hansen (2023)

timeseriesflattener: A Python package for summarizing features from (medical) time series. - Martin Bernstorff; Kenneth C. Enevoldsen; Jakob Damgaard; Andreas Danielsen; Lasse Hansen (J. Open Source Softw., 2023)

Robust and Realtime Large Deformation Ultrasound Registration Using End-to-End Differentiable Displacement Optimisation. - Mattias P. Heinrich; Hanna Siebert; Laura Graf 001; Sven Mischkewitz; Lasse Hansen (Sensors, 2023)

Learn2Reg: Comprehensive Multi-Task Medical Image Registration Challenge, Dataset and Evaluation in the Era of Deep Learning. - Alessa Hering; Lasse Hansen; Tony C. W. Mok; Albert C. S. Chung; Hanna Siebert; Stephanie Häger; Annkristin Lange; Sven Kuckertz; Stefan Heldmann; Wei Shao 008; Sulaiman Vesal; Mirabela Rusu; et al. (IEEE Trans. Medical Imaging, 2023)

TextDescriptives: A Python package for calculating a large variety of metrics from text. - Lasse Hansen; Ludvig Renbo Olsen; Kenneth C. Enevoldsen (J. Open Source Softw., 2023)

Anatomy-guided domain adaptation for 3D in-bed human pose estimation. - Alexander Bigalke; Lasse Hansen; Jasper Diesel; Carlotta Hennigs; Philipp Rostalski; Mattias P. Heinrich (Medical Image Anal., 2023)

Displacement Representation for Conditional Point Cloud Registration - HeatReg Applied to 2D/3D Freehand Ultrasound Reconstruction. - Lasse Hansen; Jürgen Lichtenstein; Mattias P. Heinrich (Bildverarbeitung für die Medizin, 2024)

Abstract: Advancing Large-scale Deformable 3D Registration with Differentiable Volumetric Rasterisation of Point Clouds - Chasing Clouds. - Mattias P. Heinrich; Alexander Bigalke; Christoph Großbröhmer; Lasse Hansen (Bildverarbeitung für die Medizin, 2024)

Abstracting Volumetric Medical Images with Sparse Keypoints for Efficient Geometric Segmentation of Lung Fissures with a Graph CNN. - Paul Kaftan; Mattias P. Heinrich; Lasse Hansen; Volker Rasche; Hans A. Kestler; Alexander Bigalke (Bildverarbeitung für die Medizin, 2024)

Implicit neural obfuscation for privacy preserving medical image sharing. - Mattias P. Heinrich; Lasse Hansen (MIDL, 2024)

SAM Carries the Burden: A Semi-Supervised Approach Refining Pseudo Labels for Medical Segmentation. - Ron Keuth; Lasse Hansen; Maren Balks; Ronja Jäger; Anne-Nele Schröder; Ludger Tüshaus; Mattias P. Heinrich (CoRR, 2024)

AcquisitionFocus: Joint Optimization of Acquisition Orientation and Cardiac Volume Reconstruction Using Deep Learning. - Christian Weihsbach; Nora Vogt; Ziad Al-Haj Hemidi; Alexander Bigalke; Lasse Hansen; Julien Oster; Mattias P. Heinrich (Sensors, 2024)

Abstract: ConvexAdam - Self-configuring Framework for Dual-Optimisation-based 3D Multitask Medical Image Registration. - Christoph Großbröhmer; Hanna Siebert; Lasse Hansen; Mattias P. Heinrich (Bildverarbeitung für die Medizin, 2025)

Autocalibration for 3D Ultrasound Reconstruction in Infant Hip Dysplasia Screening. - Wiebke Heyer; Christian Weihsbach; Christoph Otte; Jürgen Lichtenstein; Sebastian Lippross; Mattias P. Heinrich; Lasse Hansen (Bildverarbeitung für die Medizin, 2025)

Real-time Landmark Guidance for Radial Head Localization in Ultrasound Imaging. - Lennart Meyling; Christoph Großbröhmer; Jürgen Lichtenstein; Mattias P. Heinrich; Lasse Hansen (Bildverarbeitung für die Medizin, 2025)

MMTEB: Massive Multilingual Text Embedding Benchmark. - Kenneth C. Enevoldsen; Isaac Chung; Imene Kerboua; Márton Kardos; Ashwin Mathur; David Stap; Jay Gala; Wissam Siblini; Dominik Krzeminski; Genta Indra Winata; Saba Sturua; Saiteja Utpala; et al. (CoRR, 2025)

ConvexAdam: Self-Configuring Dual-Optimization-Based 3D Multitask Medical Image Registration. - Hanna Siebert; Christoph Großbröhmer; Lasse Hansen; Mattias P. Heinrich (IEEE Trans. Medical Imaging, 2025)

3d freehand ultrasound reconstruction by reference-based point cloud registration. - Christoph Großbröhmer; Lasse Hansen; Jürgen Lichtenstein; Ludger Tüshaus; Mattias P. Heinrich (Int. J. Comput. Assist. Radiol. Surg., 2025)

Sparse keypoint segmentation of lung fissures: efficient geometric deep learning for abstracting volumetric images. - Paul Kaftan; Mattias P. Heinrich; Lasse Hansen; Volker Rasche; Hans A. Kestler; Alexander Bigalke (Int. J. Comput. Assist. Radiol. Surg., 2025)

DenseSeg: joint learning for semantic segmentation and landmark detection using dense image-to-shape representation. - Ron Keuth; Lasse Hansen; Maren Balks; Ronja Jäger; Anne-Nele Schröder; Ludger Tüshaus; Mattias P. Heinrich (Int. J. Comput. Assist. Radiol. Surg., 2025)

OncoReg: Medical Image Registration for Oncological Challenges. - Wiebke Heyer; Yannic Elser; Lennart Berkel; Xinrui Song; Xuanang Xu; Pingkun Yan; Xi Jia; Jinming Duan 001; Zi Li; Tony C. W. Mok; Bowen Li; Christian Staackmann; et al. (CoRR, 2025)

Beyond the LUMIR challenge: The pathway to foundational registration models. - Junyu Chen 002; Shuwen Wei; Joel Honkamaa; Pekka Marttinen; Hang Zhang; Min Liu; Yichao Zhou; Zuopeng Tan; Zhuoyuan Wang; Yi Wang; Hongchao Zhou; Shunbo Hu; et al. (CoRR, 2025)