@article {1971,
	title = {Joint Maximum Likelihood estimation of motion and T1 parameters from magnetic resonance images in a super-resolution framework: a simulation study},
	journal = {Fundamenta Informaticae},
	volume = {172},
	year = {2020},
	pages = {105{\textendash}128},
	abstract = {Magnetic resonance imaging (MRI) based T1 mapping allows spatially resolved quantification of the tissue-dependent spin-lattice relaxation time constant T1, which is a potential biomarker of various neurodegenerative diseases, including Multiple Sclerosis, Alzheimer disease, and Parkinson{\textquoteright}s disease. In conventional T1 MR relaxometry, a quantitative T1 map is obtained from a series of T1-weighted MR images. Acquiring such a series, however, is time consuming. This has sparked the development of more efficient T1 mapping methods, one of which is a super-resolution reconstruction (SRR) framework in which a set of low resolution (LR) T1-weighted images is acquired and from which a high resolution (HR) T1 map is directly estimated. In this paper, the SRR T1 mapping framework is augmented with motion estimation. That is, motion between the acquisition of the LR T1-weighted images is modeled and the motion parameters are estimated simultaneously with the T1 parameters. Based on Monte Carlo simulation experiments, we show that such an integrated motion/relaxometry estimation approach yields more accurate T1 maps compared to a previously reported SRR based T1 mapping approach.},
	doi = {10.3233/FI-2020-1896},
	author = {Quinten Beirinckx and Gabriel Ramos-Llord{\'e}n and Ben Jeurissen and Dirk H J Poot and Paul M Parizel and Marleen Verhoye and Jan Sijbers and Arnold Jan den Dekker}
}
@article {1925,
	title = {The maximum a posteriori probability rule for atom column detection from HAADF STEM images},
	journal = {Ultramicroscopy},
	volume = {201},
	year = {2019},
	pages = {81-91},
	abstract = {Recently, the maximum a posteriori (MAP) probability rule has been proposed as an objective and quantitative method to detect atom columns and even single atoms from high-resolution high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) images. The method combines statistical parameter estimation and model-order selection using a Bayesian framework and has been shown to be especially useful for the analysis of the structure of beam-sensitive nanomaterials. In order to avoid beam damage, images of such materials are usually acquired using a limited incoming electron dose resulting in a low contrast-to-noise ratio (CNR) which makes visual inspection unreliable. This creates a need for an objective and quantitative approach. The present paper describes the methodology of the MAP probability rule, gives its step-by-step derivation and discusses its algorithmic implementation for atom column detection. In addition, simulation results are presented showing that the performance of the MAP probability rule to detect the correct number of atomic columns from HAADF STEM images is superior to that of other model-order selection criteria, including the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). Moreover, the MAP probability rule is used as a tool to evaluate the relation between STEM image quality measures and atom detectability resulting in the introduction of the so-called integrated CNR (ICNR) as a new image quality measure that better correlates with atom detectability than conventional measures such as signal-to-noise ratio (SNR) and CNR.},
	keywords = {Atom detectability, Atom detection, Model selection, Scanning transmission electron microscopy (STEM)},
	issn = {0304-3991},
	doi = {https://doi.org/10.1016/j.ultramic.2019.02.003},
	url = {http://www.sciencedirect.com/science/article/pii/S0304399118304236},
	author = {J Fatermans and Sandra Van Aert and Arnold Jan den Dekker}
}
@article {1878,
	title = {Single Atom Detection from Low Contrast-to-Noise Ratio Electron Microscopy Images},
	journal = {Phys. Rev. Lett.},
	volume = {121},
	year = {2018},
	month = {Jul},
	pages = {056101},
	abstract = {Single atom detection is of key importance to solving a wide range of scientific and technological problems. The strong interaction of electrons with matter makes transmission electron microscopy one of the most promising techniques. In particular, aberration correction using scanning transmission electron microscopy has made a significant step forward toward detecting single atoms. However, to overcome radiation damage, related to the use of high-energy electrons, the incoming electron dose should be kept low enough. This results in images exhibiting a low signal-to-noise ratio and extremely weak contrast, especially for light-element nanomaterials. To overcome this problem, a combination of physics-based model fitting and the use of a model-order selection method is proposed, enabling one to detect single atoms with high reliability.},
	doi = {10.1103/PhysRevLett.121.056101},
	url = {https://link.aps.org/doi/10.1103/PhysRevLett.121.056101},
	author = {J Fatermans and Arnold Jan den Dekker and M{\"u}ller-Caspary, K. and Ivan Lobato and O{\textquoteright}Leary, C. M. and Peter D Nellist and Sandra Van Aert}
}
@article {VanAert:gq5005,
	title = {Advanced electron crystallography through model-based imaging},
	journal = {IUCrJ},
	volume = {3},
	number = {1},
	year = {2016},
	month = {Jan},
	abstract = {The increasing need for precise determination of the atomic arrangement of non-periodic structures in materials design and the control of nanostructures explains the growing interest in quantitative transmission electron microscopy. The aim is to extract precise and accurate numbers for unknown structure parameters including atomic positions, chemical concentrations and atomic numbers. For this purpose, statistical parameter estimation theory has been shown to provide reliable results. In this theory, observations are considered purely as data planes, from which structure parameters have to be determined using a parametric model describing the images. As such, the positions of atom columns can be measured with a precision of the order of a few picometres, even though the resolution of the electron microscope is still one or two orders of magnitude larger. Moreover, small differences in average atomic number, which cannot be distinguished visually, can be quantified using high-angle annular dark-field scanning transmission electron microscopy images. In addition, this theory allows one to measure compositional changes at interfaces, to count atoms with single-atom sensitivity, and to reconstruct atomic structures in three dimensions. This feature article brings the reader up to date, summarizing the underlying theory and highlighting some of the recent applications of quantitative model-based transmisson electron microscopy.},
	keywords = {experimental design, quantitative analysis, statistical parameter estimation, structure refinement, transmission electron microscopy},
	doi = {10.1107/S2052252515019727},
	url = {http://dx.doi.org/10.1107/S2052252515019727},
	author = {Sandra Van Aert and Annick De Backer and Martinez, Gerardo T. and Arnold Jan den Dekker and Dirk Van Dyck and Sara Bals and Van Tendeloo, Gustaaf}
}
@article {1892,
	title = {EPR and DFT analysis of biologically relevant chromium(V) complexes with d-glucitol and d-glucose},
	journal = {Journal of Inorganic Biochemistry},
	volume = {162},
	year = {2016},
	pages = {216 - 226},
	keywords = {1, 2-diolato ligands, DFT, ENDOR, EPR, HYSCORE, Oxidochromium(V)},
	issn = {0162-0134},
	doi = {https://doi.org/10.1016/j.jinorgbio.2016.07.012},
	url = {http://www.sciencedirect.com/science/article/pii/S0162013416302136},
	author = {Sabine Van Doorslaer and Quinten Beirinckx and Kevin Nys and Mar{\'\i}a Florencia Mangiameli and Bert Cuypers and Freddy Callens and Henk Vrielinck and Juan Carlos Gonz{\'a}lez}
}
@article {denDekker:97,
	title = {Resolution: a survey},
	journal = {J. Opt. Soc. Am. A},
	volume = {14},
	number = {3},
	year = {1997},
	month = {Mar},
	pages = {547{\textendash}557},
	publisher = {OSA},
	abstract = {Past and present approaches to the concept of optical resolution are reviewed.},
	doi = {10.1364/JOSAA.14.000547},
	url = {http://josaa.osa.org/abstract.cfm?URI=josaa-14-3-547},
	author = {Arnold Jan den Dekker and A. van den Bos}
}
