@article {2351,
	title = {Deep Learning-Enhanced Accelerated 2D TSE and 3D Super-Resolution Dixon TSE for Rapid Comprehensive Knee Joint Assessment},
	journal = {Investigative Radiology},
	volume = {60},
	year = {2025},
	pages = {220-233},
	doi = {10.1097/RLI.0000000000001118},
	author = {Celine Smekens and Quinten Beirinckx and Frederik Bosmans and Floris Vanhevel and Annemie Snoeckx and Jan Sijbers and Ben Jeurissen and Thomas Janssens and Pieter Van Dyck}
}
@conference {2291,
	title = {Accelerated Dual-contrast Three-dimensional Knee Magnetic Resonance Imaging Using Super-resolution Reconstructed Deep Learning-enhanced Two-dimensional Dixon Turbo Spin-echo Imaging},
	volume = {27},
	year = {2023},
	month = {05/2023},
	pages = {1-24},
	publisher = {Thieme Medical Publishers, Inc.},
	abstract = {Recent work on three-dimensional (3D) super-resolution reconstruction (SRR) of conventional two-dimensional (2D) turbo spin-echo (TSE) knee magnetic resonance imaging (MRI) shows that high-resolution isotropic knee MRI is technically feasible. Yet the use of acceleration techniques and contrast optimization are needed for clinical validation of this 3D method. With the advent of deep learning (DL) image reconstruction techniques, high acceleration of SRR input data is now achievable through extended use of simultaneous multislice and parallel imaging methods. Moreover, the combination of accelerated TSE with the Dixon method allows us to acquire fat-suppressed and non-fat-suppressed data within a single acquisition that further accelerates the dual-contrast SRR protocol.

This study evaluated the technical feasibility of 3D SRR MRI based on DL-enhanced highly accelerated 2D Dixon TSE MRI. It also compared image quality and diagnostic confidence of this dual-contrast 3D technique to (accelerated) conventional 2D TSE knee MRI. We hypothesized that the SRR method provides the required contrasts needed for comprehensive knee joint evaluation in a competitive acquisition time.},
	doi = {10.1055/s-0043-1770025},
	url = {https://www.thieme-connect.com/products/ejournals/abstract/10.1055/s-0043-1770025},
	author = {Celine Smekens and Floris Vanhevel and Quinten Beirinckx and Thomas Janssens and Pieter Van Dyck}
}
@article {2275,
	title = {To shift or to rotate? Comparison of acquisition strategies for multi-slice super-resolution magnetic resonance imaging},
	journal = {Frontiers in Neuroscience},
	year = {2022},
	pages = {1-18},
	doi = {https://doi.org/10.3389/fnins.2022.1044510},
	author = {Michele Nicastro and Ben Jeurissen and Quinten Beirinckx and Celine Smekens and Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker}
}
@inproceedings {2159,
	title = {Comparison of MR acquisition strategies for super-resolution reconstruction using the Bayesian Mean Squared Error},
	booktitle = { International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine},
	year = {2021},
	abstract = {In multi-slice super-resolution reconstruction (MS-SRR), a high resolution image, referred to as SRR image, is estimated from a series of multi-slice images with a low through-plane resolution. This work proposes a framework based on the Bayesian mean squared error of the Maximum A Posteriori estimator of a SRR image to compare the accuracy and precision of two commonly adopted MR acquisition strategies in MS-SRR. The first strategy consists in acquiring a set of multi-slice
images, where each image is shifted in the through-plane direction by a different, sub-pixel distance. The latter consists in acquiring a set of multi-slice images, where each image is rotated around the frequency or phase-encoding axis by a different rotation angle. Results show that MS-SRR based on rotated multi-slice images outperforms MS-SRR based on shifted multi-slice images in terms of accuracy, precision and mean squared error of the reconstructed image.},
	author = {Michele Nicastro and Ben Jeurissen and Quinten Beirinckx and Celine Smekens and Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker}
}
@conference {2205,
	title = {High-resolution T2* mapping of the knee based on UTE Spiral VIBE MRI},
	volume = {34},
	year = {2021},
	pages = {S53-S54},
	author = {Celine Smekens and Quinten Beirinckx and Floris Vanhevel and Pieter Van Dyck and Arnold Jan den Dekker and Jan Sijbers and Thomas Janssens and Ben Jeurissen}
}
@conference {2181,
	title = {Rotated or shifted sets of multi-slice MR images for super-resolution reconstruction? A Bayesian answer},
	volume = {34},
	year = {2021},
	pages = {S56-S57},
	doi = {10.1007/s10334-021-00947-8},
	author = {Michele Nicastro and Ben Jeurissen and Quinten Beirinckx and Celine Smekens and Dirk H J Poot and Jan Sijbers and Arnold Jan den Dekker}
}
@conference {2160,
	title = {Super-resolution T2* mapping of the knee using UTE Spiral VIBE MRI},
	year = {2021},
	pages = {3920},
	abstract = {T2* mapping using ultrashort echo time (UTE) MRI allows for quantitative evaluation of collagen-rich knee structures with short mean transverse relaxation times. However, acquisitions with low through-plane resolution are commonly used to obtain T2* maps within reasonable scan times, affecting the accuracy of the estimations because of partial volume effects. In this work, model-based super-resolution reconstructions based on UTE Spiral VIBE MRI were performed to obtain high-resolution T2* maps of knee structures within a reasonable scan time. The obtained T2* maps are comparable to maps generated with direct 3D UTE Spiral VIBE acquisitions while requiring approximately 25\% less scan time.},
	author = {Celine Smekens and Quinten Beirinckx and Floris Vanhevel and Pieter Van Dyck and Arnold Jan den Dekker and Jan Sijbers and Thomas Janssens and Ben Jeurissen}
}
