Scientific Program
Aims and Scope
Submissions are invited in all areas of biomedical image registration. Topics of interest include, but are not limited to:
Novel registration methodology: Learning-based methods, combinations of learning and non-learning techniques and conventional approaches. 2D/3D/4D, spatiotemporal/dynamic, pairwise / groupwise, slice-to-volume, projective, single/multi-modal, intra/inter-subject, model-based, patch-based, multi-channel, tracking.
Machine learning and deep learning techniques for registration: unsupervised / supervised / reinforcement learning, convolutional / recurrent / transformer networks, cost correlation, neural networks for feature extraction and matching, correspondence weighting and prediction, attention modeling, deformation learning, deep encoder-decoder networks
Optimisation and mathematical aspects of image registration: continuous/discrete optimization, real-time, similarity measures, diffeomorphisms, LDDMM, stationary velocity, inverse consistency, multi-scale, graphical models
Biomedical applications of registration: computer-assisted interventions, image-guided therapy, treatment planning/delivery, diagnosis/prognosis, atlas-based segmentation, label fusion, histopathology correlation, serial studies, pathology detection and localization, morphometry, biomechanics, image retrieval/restoration/fusion, imaging biomarkers for precision medicine, radiomics & radiogenomics, early proofs of concept
Validation of registration: quantitative and qualitative methods, benchmarking, comparison studies, phantom studies, correlation to outcome, validation protocols and performance metrics, uncertainty estimation
Motion modelling, simulations and motion reconstruction
Workshop on Biomedical Image Registration 2022
| Sunday 10th July (Klinikum rechts d. Isar) | Monday 11th July (TUM Campus Garching) | Tuesday 12th July (TUM Campus Garching) | |||
| 10:00 - 10:15 | Opening Prof. Dr. Julia Schnabel | 09:15 - 10:00 | Keynote Dr. Wolfgang Wein | ||
| 10:15 - 11:00 | S1 Short Orals Chairs: Dr. Veronika Zimmer (TUM) / Dr. Matthew Toews (ÉTS) | 10:00 - 10:30 | S3 Short Orals Chairs: Prof. Žiga Špiclin (Ljubljana) / Tony Mok (CUHK) | ||
| 11:00 - 11:15 | break | 10:30 - 10:45 | break | ||
| 11:15 - 12:15 | L1 Orals: Topology / Atlases Chairs: Dr. Veronika Zimmer (TUM) / Dr. Stefan Heldmann (MEVIS) | 10:45 - 11:45 | L4 Orals: Optimisation Chairs: Prof. Žiga Špiclin (Ljubljana) / Tony Mok (CUHK) | ||
| 12:15 - 13:00 | Keynote Prof. Dr. Josien Pluim | 11:45 - 12:30 | Keynote Prof. Dr. Maria Vakalopoulou | ||
| 13:00 - 14:00 | break | 12:30 - 13:15 | break | ||
| 14:00 - 15:30 | Tutorial: Medical Image Registration Dr. Veronika Zimmer | 14:00 - 14:30 | S2 Short Orals Chairs: Prof. Stefan Klein (Erasmus), Prof. Xiahai Zhang (Fudan) | 13:15 - 14:15 | L5 Orals: Metrics / Losses Chairs: Alessa Hering (Radboud) / Prof. Adrian Dalca (Harvard/MIT) |
| 14:30 - 15:30 | L2 Orals: Uncertainty Chairs: Prof. Stefan Klein (Erasmus), Prof. Pew-Thian Yap (UNC) | 14:15 - 14:30 | Awards Prof. Dr. Daniel Rueckert | ||
| 15:30 - 16:00 | break | 15:30 - 15:45 | break | 14:30 - 15:15 | Poster |
| 16:00 - 18:00 | Learn2Reg Challenge Prof. Mattias Heinrich | 15:45 - 16:45 | L3 Orals: Architectures Chairs: Dr. Raphael Prevost (ImFusion), Prof. Kilian Pohl (Stanford) | ||
| 16:45 - 17:45 | Poster | ||||
| 19:00 - | Conference Dinner: Paulaner Nockherberg |
| L1 Orals: Atlases / Topology | Julia Andresen: Unsupervised Non-Correspondence Detection in Medical Images Using an Image Registration Convolutional Neural Network, [Poster], [Video]. |
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| Mon 11:15-12:15 | Anton François: Weighted Metamorphosis for registration of images with different topology, [Poster], [Video]. |
| Ubaldo Ramon Julvez: LDDMM meets GANs: Generative Adversarial Networks for diffeomorphic registration, [Poster], [Video]. | |
| Wietske Bastiaansen: Towards a 4D Spatio-Temporal Atlas of the Embryonic and Fetal Brain using a Deep Learning approach for Groupwise Image Registration, [Poster], [Video]. |
| L2 Orals: Uncertainty | Christian Weihsbach: DeepSTAPLE: Learning to predict multimodal registration quality for unsupervised domain adaptation, [Poster], [Video]. |
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| Mon 14:30-15:30 | Alphin J Thottupattu: A method for image registration via broken geodesics, [Poster], [Video]. |
| Andreas Smolders: Deformable Image Registration uncertainty quantification using deep learning for dose accumulation in adaptive proton therapy, [Poster], [Video]. | |
| Frithjof Kruggel: Distinct structural patterns of the human brain: A caveat for registration, [Poster], [Video]. |
| L3 Orals: Architectures | Samuel Joutard: A multi-organ point cloud registration algorithm for abdominal CT registration, [Poster], [Video]. |
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| Mon 15:45-16:45 | Mattias P Heinrich: Voxelmorph++ Going beyond the cranial vault with keypoint supervision and multi-channel instance optimisation, [Poster], [Video]. |
| Junyu Chen: Unsupervised Learning of Diffeomorphic Image Registration via TransMorphn, [Poster], [Video]. | |
| Sean I. Young, Yaël Balbastre: SuperWarp: Supervised Learning and Warping on U-Net for Invariant Subvoxel-Precise Registration, [Poster], [Video]. |
| L5 Orals: Metrics / Losses | Ivor J A Simpson: Motion Correction in low SNR MRI using an approximate Rician log-likelihood, [Poster], [Video]. |
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| Tue 13:00-14:00 | Johan Öfverstedt: Cross-Sim-NGF: FFT-Based Global Rigid Multimodal Alignment of Image Volumes using Normalized Gradient Fields, [Poster], [Video]. |
| Justinas Antanavicius, Raghavendra Selvan: Identifying Partial Mouse Brain Microscopy Images from the Allen Reference Atlas using a Contrastively Learned Semantic Space, [Poster], [Video]. | |
| Xinrui Song: Transformed Grid Distance Loss for Supervised Image Registration, [Poster], [Video]. |
| S1 Short Orals | Jing Zou: Deformable Lung CT Registration by Decomposing the Large Deformation, [Poster], [Video]. |
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| Mon 10:15-11:00 | Alexander Bigalke: A novel Mean Teacher framework for domain adaptive lung registration, [Poster], [Video]. |
| Lihao Liu: You Only Look at Patches: A Patch-wise Framework for 3D Unsupervised Medical Image Registration, [Poster], [Video]. | |
| Zicong Zhou: Recent Developments of an Optimal Control approach to Nonrigid Image Registration, [Poster], [Video]. |
| S2 Short Orals | Batool Abbas: 2D/3D Intermodel Registration of Quantitative Magnetic Resonance Images, [Poster], [Video]. |
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| Mon 14:00-14:30 | Andjela Dimitrijevic: Deep Learning-based Longitudinal Intra-subject Registration of Pediatric Brain MR Images, [Poster], [Video] |
| Neha Goyal: Real-time Alignment for Connectomics, [Poster], [Video]. |
| S3 Short Orals | Philippe Weitz, Leslie Solorzano: ACROBAT - Automatic Registration of Breast Cancer Tissue, [Poster], [Video]. |
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| Tue 10:00-10:45 | Mona Schumacher: Weak Bounding Box Supervision for Image Registration Networks, [Poster], [Video]. |
| Annkristin Lange: A deformable image-based registration approach to obtain shape correspondence for statistical shape modeling of finger bones, [Poster], [Video]. |
List of Accepted Long Papers
Title | Authors | Affiliation (first author) |
LDDMM meets GANs: Generative Adversarial Networks for diffeomorphic registration | Ubaldo Ramon Julvez|Monica Hernandez|Elvira Mayordomo | Universidad de Zaragoza |
Cross domain knowledge compression in realtime optical flow prediction on ultrasound sequences | Till Nicke|Laura Graf|Mikko Lauri|Sven Mischkewitz|Simone Frintrop|Mattias P Heinrich | Fraunhofer MEVIS Lübeck |
Cross-Sim-NGF: FFT-Based Global Rigid Multimodal Alignment of Image Volumes using Normalized Gradient Fields | Johan Öfverstedt|Joakim Lindblad|Natasa Sladoje | Uppsala University |
Multi-magnification networks for deformable image registration on histopathology images | Oezdemir Cetin|Yiran Shu|Nadine Flinner|Paul Ziegler|Peter Wild|Heinz Koeppl | Technische Universität Darmstadt |
Deformable Image Registration uncertainty quantification using deep learning for dose accumulation in adaptive proton therapy | Andreas Smolders|Antony lomax|Damien Charles Weber|Francesca Albertini | ETH Zurich |
DeepSTAPLE: Learning to predict multimodal registration quality for unsupervised domain adaptation | Christian Weihsbach|Alexander Bigalke|Christian N. Kruse|Hellena Hempe|Mattias P Heinrich | Universität zu Lübeck |
A multi-organ point cloud registration algorithm for abdominal CT registration | Samuel Joutard|Thomas Pheiffer|Chloe Audigier|Patrick Wohlfahrt|Reuben Dorent|Sebastien Piat|Markus Juergens|Tom Vercauteren|Marc Modat|Tommaso Mansi | King's College London |
A method for image registration via broken geodesics | Alphin J Thottupattu|Jayanthi Sivaswamy|Venkateswaran P. Krishnan | International Institute of Information Technology Hyderabad |
Voxelmorph++ Going beyond the cranial vault with keypoint supervision and multi-channel instance optimisation | Mattias P Heinrich|Lasse Hansen | Universität zu Lübeck |
Motion Correction in low SNR MRI using an approximate Rician log-likelihood | Ivor J A Simpson|Balazs Orzsik|Iris Asllani|Mara Cercignani | University of Sussex |
Weighted Metamorphosis for registration of images with different topology. | Anton François|Matthis Maillard|Catherine Oppenheim|Johan Pallud|Pietro Gori|Joan Alexis Glaunès | University Paris Descartes |
Identifying Partial Mouse Brain Microscopy Images from the Allen Reference Atlas using a Contrastively Learned Semantic Space | Justinas Antanavicius|Roberto Leiras|Raghavendra Selvan | University of Copenhagen |