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Modulation Transfer Function (modulation + transfer_function)
Selected AbstractsReconstruction of a yeast cell from X-ray diffraction dataACTA CRYSTALLOGRAPHICA SECTION A, Issue 4 2006Pierre Thibault Details are provided of the algorithm used for the reconstruction of yeast cell images in the recent demonstration of diffraction microscopy by Shapiro, Thibault, Beetz, Elser, Howells, Jacobsen, Kirz, Lima, Miao, Nieman & Sayre [Proc. Natl Acad. Sci. USA (2005), 102, 15343,15346]. Two refinements of the iterative constraint-based scheme are developed to address the current experimental realities of this imaging technique, which include missing central data and noise. A constrained power operator is defined whose eigenmodes allow the identification of a small number of degrees of freedom in the reconstruction that are negligibly constrained as a result of the missing data. To achieve reproducibility in the algorithm's output, a special intervention is required for these modes. Weak incompatibility of the constraints caused by noise in both direct and Fourier space leads to residual phase fluctuations. This problem is addressed by supplementing the algorithm with an averaging method. The effect of averaging may be interpreted in terms of an effective modulation transfer function, as used in optics, to quantify the resolution. The reconstruction details are prefaced with simulations of wave propagation through a model yeast cell. These show that the yeast cell is a strong-phase-contrast object for the conditions in the experiment. [source] A toolkit for the characterization of CCD cameras for transmission electron microscopyACTA CRYSTALLOGRAPHICA SECTION D, Issue 1 2010M. Vulovic Charge-coupled devices (CCD) are nowadays commonly utilized in transmission electron microscopy (TEM) for applications in life sciences. Direct access to digitized images has revolutionized the use of electron microscopy, sparking developments such as automated collection of tomographic data, focal series, random conical tilt pairs and ultralarge single-particle data sets. Nevertheless, for ultrahigh-resolution work photographic plates are often still preferred. In the ideal case, the quality of the recorded image of a vitrified biological sample would solely be determined by the counting statistics of the limited electron dose the sample can withstand before beam-induced alterations dominate. Unfortunately, the image is degraded by the non-ideal point-spread function of the detector, as a result of a scintillator coupled by fibre optics to a CCD, and the addition of several inherent noise components. Different detector manufacturers provide different types of figures of merit when advertising the quality of their detector. It is hard for most laboratories to verify whether all of the anticipated specifications are met. In this report, a set of algorithms is presented to characterize on-axis slow-scan large-area CCD-based TEM detectors. These tools have been added to a publicly available image-processing toolbox for MATLAB. Three in-house CCD cameras were carefully characterized, yielding, among others, statistics for hot and bad pixels, the modulation transfer function, the conversion factor, the effective gain and the detective quantum efficiency. These statistics will aid data-collection strategy programs and provide prior information for quantitative imaging. The relative performance of the characterized detectors is discussed and a comparison is made with similar detectors that are used in the field of X-ray crystallography. [source] Evaluation of the improved three-dimensional resolution of a synchrotron radiation computed tomograph using a micro-fabricated test patternJOURNAL OF SYNCHROTRON RADIATION, Issue 6 2008Ryuta Mizutani A micro test pattern prepared by focused ion beam milling was used to evaluate the three-dimensional resolution of a microtomograph at the BL20B2 beamline of SPring-8. The resolutions along the direction within the tomographic slice plane and perpendicular to it were determined from the modulation transfer functions. The through-plane resolution perpendicular to the tomographic slice was evaluated to be 8,µm, which corresponds to the spatial resolution of two-dimensional radiographs. In contrast, the in-plane resolution within the slice was evaluated to be 12,µm. Real-space interpolation was performed prior to the tomographic reconstruction, giving an improved in-plane resolution of 8.5,µm. However, the 8,µm pitch pattern was resolved in the interpolated slice image. To reflect this result, another resolution measure from the peak-to-valley difference plot was introduced. This resolution measure gave resolution limits of 7.4,µm for the in-plane direction and 6.1,µm for the through-plane direction. The three-dimensional test pattern along with the interpolated reconstruction enables the quantitative evaluation of the spatial resolution of microtomographs. [source] Temporal detection in human vision: dependence on eccentricityOPHTHALMIC AND PHYSIOLOGICAL OPTICS, Issue 2 2002R. F. Hess Studies of human perception of time-varying luminance often aim to estimate either temporal impulse response shapes or temporal modulation transfer functions (MTFs) of putative temporal processing mechanisms. Previously, temporal masking data have been used to estimate the properties and numbers of these temporal mechanisms in central vision for 1 cycle per degree (cpd) targets [Fredericksen and Hess (1998)]. The same methods have been used to explore how these properties change with stimulus energy [Fredericksen and Hess (1997)] and spatial frequency [Fredericksen and Hess (1999)]. We present here analyses of the properties of temporal mechanisms that detect temporal variations of luminance in peripheral vision. The results indicate that a two-filter model provides the best model for our masking data, but that no multiple filter model provides an acceptable fit across the range of parameters varied in this study. Single-filter modelling shows differences between processing mechanisms at 1 cpd in central vision and those that operate eccentrically. We find evidence that this change is because of differences in relative sensitivities of the mechanisms, and to differences in fundamental mechanism impulse responses. [source] | ||||||||||