Maria E. Rudnaya
Eindhoven University of Technology
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Publication
Featured researches published by Maria E. Rudnaya.
Ultramicroscopy | 2011
Maria E. Rudnaya; W. Van den Broek; R.M.P. Doornbos; R.M.M. Mattheij; J.M.L. Maubach
A new simultaneous autofocus and twofold astigmatism correction method is proposed for High Angle Annular Dark Field Scanning Transmission Electron Microscopy (HAADF-STEM). The method makes use of a modification of image variance, which has already been used before as an image quality measure for different types of microscopy, but its use is often justified on heuristic grounds. In this paper we show numerically that the variance reaches its maximum at Scherzer defocus and zero astigmatism. In order to find this maximum a simultaneous optimization of three parameters (focus, x- and y-stigmators) is necessary. This is implemented and tested on a FEI Tecnai F20. It successfully finds the optimal defocus and astigmatism with time and accuracy, compared to a human operator.
Microscopy and Microanalysis | 2009
Maria E. Rudnaya; R.M.M. Mattheij; J.M.L. Maubach
Introduction. A robust and reliable autofocus algorithm is important concern for the automation of a Scanning Electron Microscope (SEM). Comparison of existing autofocus techniques has been done for specific specimen for fluorescence [1] and non-fluorescence microscopy [2-3]. For Scanning Transmission Electron Microscopy some of available algorithms were compared [4]. To the authors’ knowledge broad evolution has not been published yet for SEM.
Journal of Mathematical Imaging and Vision | 2012
Maria E. Rudnaya; Hg Hennie ter Morsche; J.M.L. Maubach; Robert M. M. Mattheij
Most automatic focusing methods are based on a sharpness function, which delivers a real-valued estimate of an image quality. In this paper, we study an L2-norm derivative-based sharpness function, which has been used before based on heuristic consideration. We give a more solid mathematical foundation for this function and get a better insight into its analytical properties. Moreover an efficient autofocus method is presented, in which an artificial blur variable plays an important role.We show that for a specific choice of the artificial blur control variable, the function is approximately a quadratic polynomial, which implies that after the recording of at least three images one can find the approximate position of the optimal defocus. This provides the speed improvement in comparison with existing approaches, which usually require recording of more than ten images for autofocus. The new autofocus method is employed for the scanning transmission electron microscopy. To be more specific, it has been implemented in the FEI scanning transmission electron microscope and its performance has been tested as a part of a particle analysis application.
world congress on engineering | 2011
Maria E. Rudnaya; R.M.M. Mattheij; J.M.L. Maubach; H.G. ter Morsche
IAENG International Journal of Computer Science | 2011
Maria E. Rudnaya; Robert Ochshorn
Nonlinear Analysis-real World Applications | 2014
Kundan Kumar; Maxim Pisarenco; Maria E. Rudnaya; Valeriu Savcenco
CASA-report | 2011
Maria E. Rudnaya; H.G. ter Morsche; J.M.L. Maubach; Robert M. M. Mattheij
Engineering Fracture Mechanics | 2009
Maria E. Rudnaya; Jml Jos Maubach
Microscopy and Microanalysis | 2011
Maria E. Rudnaya; W. Van den Broek; R.M.P. Doornbos; Sc Kho; R.M.M. Mattheij; Joseph Maubach
Higher Education | 2011
Maria E. Rudnaya