6 abstracts accepted for ISMRM 2022

6 abstracts have been accepted for presentation at the coming ISMRM 2022 conference:

S. Amirrajab, C. Lorenz, J. Weese, J. Pluim, M. Breeuwer. “Intra- and intersubject synthesis of cardiac MR images using a VAE and GAN”

S. Amirrajab, Y. Al Khalil, C. Lorenz, J. Weese, J. Pluim, M. Breeuwer. “sim2real: Cardiac MR image simulation-to-real translation via unsupervised GANs”

Y. Al Khalil, A. Ayaz, C. Lorenz, J. Weese, J. Pluim, M. Breeuwer. “Reducing the impact of texture on deep-learning brain tissue segmentation networks trained with simulated MR images”

Y. Al Khalil, S. Amirrajab, C. Lorenz, J. Weese, J. Pluim, M. Breeuwer, “Late feature fusion and GAN-based augmentation for generalizable cardiac MRI segmentation”

A. Ayaz, K. Lukassen, C. Lorenz, J. Weese, M. Breeuwer. “Brain MR image super resolution using simulated data to perform in real-world MRI”

A. Ayaz, R. Jong, S. Abbasi-Sureshjani, S. Amirrajab, C. Lorenz, J. Weese, M. Breeuwer. “3D brain MRI synthesis utilizing 2D SPADE-GAN and 3D CNN architecture”

See also our publication list

First version of public database

The first version of the openGTN public database with simulated and synthesized MRI data will be made available on 31 December 2020. The database will contain cardiac, brain and spine data without pathology. Data with pathology is planned for March 2021. More information about the database can be found here.

5 abstracts accepted for ISMRM 2020

Five abstracts have been accepted for poster presentation at the 28th Annual Meeting of the International Society of Magnetic Resonance in Medicine (ISMRM). The meeting was supposed to take place in May 2020 in Sydney, Australia, but was rescheduled to 8-13 August in Paris, France. The abstract titles can be found here.

Paper accepted by the prestigious MIDL 2020 conference

4D Semantic Cardiac Magnetic Resonance Image Synthesis on XCAT Anatomical Model

Available on Openreview and arXiv.

We are thrilled to share with you our recent paper accepted for @midl_conference 2020 presenting a novel hybrid controllable image generation method for synthesizing anatomically meaningful 3D+t labelled CMR images. Check out how we efficiently combine a physics-driven anatomical model with a SOTA data-driven generative adversarial network to generate realistic-looking cardiac MR images. As a part of the OpenGTN research, we step towards tackling the limited availability of medical data for deep learning training.

openGTN workshop cancelled due to outbreak Corona virus

With much regret we have to inform you that we have to cancel the openGTN Workshop planned for 27 March 2020. Especially in the province of Noord-Brabant, in which Eindhoven is located, we have a significant outbreak of the Corona virus. As a consequence, Dutch government has recommended to work as much as possible at home and avoid unnecessary contacts. We hope we can reschedule the workshop before Summer 2020, and we hope that you will then still be interested to attend.