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, Montreal, Canada

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, 28th Annual Meeting, 8-13 August, Paris, France

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

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

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

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

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)


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