Scientific program

Preliminary program of the 2-day workshop

Registration

On-site registration and badge pick-up

Welcome note from the WBIR 2020 organization committee

Oral session: Robust initialization and acceleration

  • Nonlinear alignment of whole tractograms with the linear assignment problem

  • Learning-based affine registration of histological images

  • Enabling manual intervention for otherwise automated registration of large image series

  • Towards segmentation and spatial alignment of the human embryonic brain using deep learning for atlas-based registration

Coffee break and poster session

Oral session: Intra-subject registration for information fusion

  • Multi-channel image registration of cardiac MR using supervised feature learning with convolutional encoder-decoder network

  • Multi-channel registration for diffusion MRI: longitudinal analysis for the neonatal brain

  • An image registration-based method for EPI distortion Correction based on Opposite Phase Encoding (COPE)

Lunch

Keynote and Oral session: Image registration in radiotherapy

  • Keynote speaker and title will be announced soon

  • Learning deformable image registration with structure guidance constraints for adaptive radio therapy

Coffee break and poster session

Oral session: Multi-channel image registration

  • Diffusion tensor driven image registration: a deep learning approach

  • Multimodal MRI template creation in the ring-tailed lemur and rhesus macaque

WBIR2020 social event with buffet dinner

Plenary sessions

  • Plenary speaker and title will be announced soon

  • Sebastien Ourselin: Translating medical imaging research towards real-world clinical applications

Coffee break and poster session

Oral session: Interventional and landmark based registration

  • Multilevel 2D-3D intensity-based image registration

  • Towards automated spine mobility quantification: a locally rigid CT to X-ray registration framework

  • Reinforced redetection of landmark in pre- and post-operative brain scan using anatomical guidance for image alignment

  • Deep volumetric feature encoding for biomedical images

Lunch

Oral session: Discontinuity preserving registration

  • An unsupervised learning approach to discontinuity-preserving image registration

  • An image registration framework for discontinuous mappings along cracks

Coffee break and poster session

Keynote and Panel discussion

  • Mattias Heinrich: How to make deep learning work in medical image registration, current advances, pitfalls and remaining challenges

  • Panel discussion and closing remarks

Keynotes

The following keynote presentations will be given during WBIR2020:

Translating medical imaging research towards real-world clinical applications

Sebastien Ourselin, King's College London


Biography:

Seb Ourselin is Head of the School of Biomedical Engineering & Imaging Sciences, King’s College London; dedicated to the development, translation and clinical application of medical imaging, computational modelling, minimally invasive interventions and surgery. In collaboration with Guy’s & St Thomas’ NHS Foundation Trust (GSTT), he is leading the establishment of the MedTech Hub, located at St Thomas’ campus. The vision of the MedTech Hub is to create a unique infrastructure that will develop health technologies including AI, medical devices, workforce and operational improvements that will be of global significance.

Previously, he was based at UCL where he formed and led numerous activities including the UCL Institute of Healthcare Engineering, the EPSRC Centre for Doctoral Training in Medical Imaging and Wellcome EPSRC Centre for Surgical and Interventional Sciences.

He is co-founder of Brainminer, an academic spin-out commercialising machine learning algorithms for brain image analysis. Their clinical decision support system for dementia diagnosis, DIADEM, obtained CE marking.

Over the last 15 years, he has raised over £50M as Principal Investigator and has published over 420 articles (over 20,000 citations, h-index 73). He is/was an associate editor for IEEE Transactions on Medical Imaging, Journal of Medical Imaging, Nature Scientific Reports, and Medical Image Analysis. He has been active in conference organisation (12 international conferences as General or Program Chair) and professional societies (APRS, MICCAI). He was elected Fellow of the MICCAI Society in 2016.


Professor Ourselin’s LinkedIn Profile

How to make deep learning work in medical image registration, current advances, pitfalls and remaining challenges

Mattias Heinrich, University of Lübeck


Biography:

Mattias Heinrich is Associate Professor for Medical Image Analysis at the Institute of Medical Informatics at the University of Lübeck. He leads a group on Medical Deep Learning with 8 researchers and enjoys teaching (under)graduate students how to implement solutions to vision problems. Since starting his doctorate in 2009 with Julia Schnabel at the University of Oxford, his passion is medical image registration. He co-organised WBIR 2016 in Las Vegas, the tutorial Learn2Reg at MICCAI 2019 and a multi-task registration challenge at MICCAI 2020. In 2021 he will be co-chair of MIDL in Lübeck.

He and his team strive to push the boundaries of medical image registration and improve its capabilities for clinical applications as well as develop novel theoretical concepts. In 2011 he won the prestigious MICCAI Young Scientist Award for MIND for multimodal registration. His work on large-displacement discrete registration (deeds) led to the 1st place in the EMPIRE10 challenge. To date, he has published 16 MICCAI papers and more than 25 journal articles (many of them in MedIA and TMI with >2500 citations and an h-index of 23). As principal investigator, he has acquired multiple competitive grants (1.7M€ over the last 5 years) for basic research projects mostly involving machine learning and image registration. He is currently looking for new talents to join his group.


Professor Heinrich's Personal Webpage