Publications

Publications about MRI simulation

Recommended reading:

H.A. Nieuwstadt et al., Numerical Simulations of Carotid MRI Quantify the Accuracy in Measuring Atherosclerotic Plaque Components In Vivo, Magn Reson Med 72:188–201 (2014)

H.A. Nieuwstadt et al., A Computer-Simulation Study on the Effects of MRI Voxel Dimensions on Carotid Plaque Lipid-Core and Fibrous Cap Segmentation and Stress Modeling, PLOS ONE | DOI:10.1371 / journal.pone.0123031 April 9, 2015 (open access)

T. Stoecker et al., High-performance computing MRI simulations. Magn Reson Med 64:186–193 (2010) (see also the JEMRIS website)

More info on MRI simulation can be found here

Publications by the openGTN project

ISMRM Benelux conference, 24 January 2020, Arnhem, The Netherlands

Aymen Ayaz et al., Pipeline for simulating realistic anatomically variable normal young, aging and diseased brain MRI  (abstract | poster)

Sina Amirrajab et al., Towards generating realistic and heterogeneous cardiac MR simulated image database for deep-learning based segmentation (abstract | poster)

Yasmina Al Khalil et al., Improving the generalization capability of deep-learning based algorithms for ventricular cavity segmentation using simulated CMR images (abstract)

Medical Imaging with Deep Learning (MIDL) conference, 6-8 July 2020, online meeting

Samaneh Abbasi-Sureshjani, Sina Amirrajab, Cristian Lorenz, Juergen Weese, Josien Pluim, Marcel Breeuwer , 4D Semantic Cardiac Magnetic Resonance Image Synthesis on XCAT Anatomical Model (oral), available on Openreview and arXiv

International Society of Magnetic Resonance in Medicine (ISMRM),
28th Annual Meeting, 8-13 August, online meeting

Sina Amirrajab et al., Towards Realistic Cardiac MR Image Simulation; Inclusion of the Endocardial Trabeculae in the XCAT Heart Anatomy (Poster 2207)

Sina Amirrajab et al., Generation of realistic and heterogeneous virtual population of cardiovascular magnetic resonance simulated images (Poster 2209)

Aymen Ayaz et al., Realistic MRI simulation pipeline for anatomically variable normal young, aging and diseased brain (Poster 1871)

Yasmina Al Khalil et al., Simulated CMR images can improve the performance and generalization capability of deep learning-based segmentation algorithms (Poster 3519)

Yasmina Al Khalil et al., Addressing the need for less MRI sequence dependent DL-based segmentation methods: model generalization to multi-site and multi-scanner data (Poster 3560)

European Society of Magnetic Resonance in Medicine and Biology (ESMRMB), September 30 – October 2, 2020 (online meeting)

Yasmina Al Khalil et al., Automated multimodal segmentation of paraspinal muscles based on chemical shift encoding-based water/fat-separated images (ePoster P01.25)

Sina Amirrajab et al., A Multipurpose Numerical Simulation Tool for Late Gadolinium Enhancement Cardiac MR Imaging (Lightning Talk L01.83)

Aymen Ayaz et al. Simulating realistic appearing multiple contrast brain MRI (Lightning Talk L01.80)

Evianne Kruithof, Sina Amirrajab et al., Influence of Image Artifacts on Image-Based Electrophysiological Simulations Using Simulated XCAT Phantom MR Images (Lightning Talk L01.35)

Medical Image Computing and Compter-Assisted Interventions (MICCAI) conference, 4-8 October 2020 (online meeting)

Amirrajab, et al. “XCAT-GAN for Synthesizing 3D Consistent Labeled Cardiac MR Images on Anatomically Variable XCAT Phantoms” (oral)

SASHIMI 2020, a MICCAI 2020 Workshop, Al Khalil, Y. Amirrajab, S. et al. “Heterogeneous Virtual Population of Simulated CMR Images for Improving the Generalization of Cardiac Segmentation Algorithms”

 

 

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