17,551 research outputs found
Dose, exposure time, and resolution in Serial X-ray Crystallography
The resolution of X-ray diffraction microscopy is limited by the maximum dose
that can be delivered prior to sample damage. In the proposed Serial
Crystallography method, the damage problem is addressed by distributing the
total dose over many identical hydrated macromolecules running continuously in
a single-file train across a continuous X-ray beam, and resolution is then
limited only by the available molecular and X-ray fluxes and molecular
alignment. Orientation of the diffracting molecules is achieved by laser
alignment. We evaluate the incident X-ray fluence (energy/area) required to
obtain a given resolution from (1) an analytical model, giving the count rate
at the maximum scattering angle for a model protein, (2) explicit simulation of
diffraction patterns for a GroEL-GroES protein complex, and (3) the frequency
cut off of the transfer function following iterative solution of the phase
problem, and reconstruction of an electron density map in the projection
approximation. These calculations include counting shot noise and multiple
starts of the phasing algorithm. The results indicate counting time and the
number of proteins needed within the beam at any instant for a given resolution
and X-ray flux. We confirm an inverse fourth power dependence of exposure time
on resolution, with important implications for all coherent X-ray imaging. We
find that multiple single-file protein beams will be needed for sub-nanometer
resolution on current third generation synchrotrons, but not on fourth
generation designs, where reconstruction of secondary protein structure at a
resolution of 0.7 nm should be possible with short exposures.Comment: 19 pages, 7 figures, 1 tabl
Incorporating Relaxivities to More Accurately Reconstruct MR Images
Purpose
To develop a mathematical model that incorporates the magnetic resonance relaxivities into the image reconstruction process in a single step.
Materials and methods
In magnetic resonance imaging, the complex-valued measurements of the acquired signal at each point in frequency space are expressed as a Fourier transformation of the proton spin density weighted by Fourier encoding anomalies: T2⁎, T1, and a phase determined by magnetic field inhomogeneity (∆B) according to the MR signal equation. Such anomalies alter the expected symmetry and the signal strength of the k-space observations, resulting in images distorted by image warping, blurring, and loss in image intensity. Although T1 on tissue relaxation time provides valuable quantitative information on tissue characteristics, the T1 recovery term is typically neglected by assuming a long repetition time. In this study, the linear framework presented in the work of Rowe et al., 2007, and of Nencka et al., 2009 is extended to develop a Fourier reconstruction operation in terms of a real-valued isomorphism that incorporates the effects of T2⁎, ∆B, and T1. This framework provides a way to precisely quantify the statistical properties of the corrected image-space data by offering a linear relationship between the observed frequency space measurements and reconstructed corrected image-space measurements. The model is illustrated both on theoretical data generated by considering T2⁎, T1, and/or ∆B effects, and on experimentally acquired fMRI data by focusing on the incorporation of T1. A comparison is also made between the activation statistics computed from the reconstructed data with and without the incorporation of T1 effects.
Result
Accounting for T1 effects in image reconstruction is shown to recover image contrast that exists prior to T1 equilibrium. The incorporation of T1 is also shown to induce negligible correlation in reconstructed images and preserve functional activations.
Conclusion
With the use of the proposed method, the effects of T2⁎ and ∆B can be corrected, and T1 can be incorporated into the time series image-space data during image reconstruction in a single step. Incorporation of T1 provides improved tissue segmentation over the course of time series and therefore can improve the precision of motion correction and image registration
Gaussian process regression can turn non-uniform and undersampled diffusion MRI data into diffusion spectrum imaging
We propose to use Gaussian process regression to accurately estimate the
diffusion MRI signal at arbitrary locations in q-space. By estimating the
signal on a grid, we can do synthetic diffusion spectrum imaging:
reconstructing the ensemble averaged propagator (EAP) by an inverse Fourier
transform. We also propose an alternative reconstruction method guaranteeing a
nonnegative EAP that integrates to unity. The reconstruction is validated on
data simulated from two Gaussians at various crossing angles. Moreover, we
demonstrate on non-uniformly sampled in vivo data that the method is far
superior to linear interpolation, and allows a drastic undersampling of the
data with only a minor loss of accuracy. We envision the method as a potential
replacement for standard diffusion spectrum imaging, in particular when
acquistion time is limited.Comment: 5 page
Towards optical intensity interferometry for high angular resolution stellar astrophysics
Most neighboring stars are still detected as point sources and are beyond the
angular resolution reach of current observatories. Methods to improve our
understanding of stars at high angular resolution are investigated. Air
Cherenkov telescopes (ACTs), primarily used for Gamma-ray astronomy, enable us
to increase our understanding of the circumstellar environment of a particular
system. When used as optical intensity interferometers, future ACT arrays will
allow us to detect stars as extended objects and image their surfaces at high
angular resolution.
Optical stellar intensity interferometry (SII) with ACT arrays, composed of
nearly 100 telescopes, will provide means to measure fundamental stellar
parameters and also open the possibility of model-independent imaging. A data
analysis algorithm is developed and permits the reconstruction of high angular
resolution images from simulated SII data. The capabilities and limitations of
future ACT arrays used for high angular resolution imaging are investigated via
Monte-Carlo simulations. Simple stellar objects as well as stellar surfaces
with localized hot or cool regions can be accurately imaged.
Finally, experimental efforts to measure intensity correlations are
expounded. The functionality of analog and digital correlators is demonstrated.
Intensity correlations have been measured for a simulated star emitting
pseudo-thermal light, resulting in angular diameter measurements. The StarBase
observatory, consisting of a pair of 3 m telescopes separated by 23 m, is
described.Comment: PhD dissertatio
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