Photoacoustic tomography is a rapidly emerging imaging technique that can benefit a wide range of biomedical applications. In this method, illumination of an object with a pulsed optical field induces an acoustic pres...
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ISBN:
(纸本)9780819482969
Photoacoustic tomography is a rapidly emerging imaging technique that can benefit a wide range of biomedical applications. In this method, illumination of an object with a pulsed optical field induces an acoustic pressure wave related to the heating of the object (optical absorption). from knowledge of the resultant pressure wave measured in a region away from the acoustic source, the object's spatially varying optical absorption properties are estimated by use of an imagereconstruction algorithm. Most existing analytic reconstruction algorithms for photoacoustic tomography assume the object of interest possesses homogeneous acoustic properties. In this work, photoacoustic tomography is considered in the case that the primary acoustic source is embedded in a planar layered medium whose speed of sound and densities are known. Exact propagation models valid for acoustic wave propagation in dispersive and absorptive layered media are presented that account for multiple reflections between the layers. Using the angular spectrum method, an inversion model is presented for acoustic data acquired on a plane parallel to the layered medium. The acquired data are shown to be simple linear combinations of plane waves generated at the source.
In order to understand at the atomic level how a biological macromolecule functions, a detailed knowledge of its 3-dimensional structure is essential. Unlike soluble proteins, integral membrane proteins are usually re...
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ISBN:
(纸本)0819437689
In order to understand at the atomic level how a biological macromolecule functions, a detailed knowledge of its 3-dimensional structure is essential. Unlike soluble proteins, integral membrane proteins are usually recalcitrant to the growth of large, well-ordered 3-D crystals, which is necessary for high-resolution x-ray crystallographic analyses. An alternative approach is to grow thin, one-molecule thick 2-D crystals in lipid bilayers and apply electron crystallography to solve the structures. Lipids surround the membrane protein in such a 2-D crystal, which allows for a direct assay of function. Another notable advantage of electron crystallography is that phases can be directly obtained from the images unlike in the case of xray where phases must be determined indirectly by methods such as isomorphous replacement etc. The availability of the phase information partially compensates for the lack of data at the highest resolution (typically similar to3.5 Angstrom and beyond) because of low-contrast in the images. We briefly review the method of recording high-resolution datafrom many tilted views of a 2-D crystal, merging of phase and amplitudes fromimages and diffraction patterns respectively and the calculation of a 3-D density map. The results from such an analysis applied to the human water channel is discussed in the context of its structure/function relationship.
The problem of reconstructing the magnitude of a complex-valued imagefromincomplete phase data of its Fourier transform is investigated. This is done by formulating the problem as passing the image through a bandpas...
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ISBN:
(纸本)0879426004
The problem of reconstructing the magnitude of a complex-valued imagefromincomplete phase data of its Fourier transform is investigated. This is done by formulating the problem as passing the image through a bandpass filter of bandwidth Δ corresponding to the data sample size and evaluating the magnitude of the resulting image. It is revealed that the reconstruction is essentially equivalent to the magnitude of the resulting image obtained by passing the original magnitude function through a set of two-dimensional extended all-pass filters. The concept of an extended all-pass filter is introduced to describe a filter whose amplitude response spreads over the whole frequency space with random variations. It is shown that the quality of the reconstruction is content-dependent and improves with increase of the sample size.
The central problem in the determination of protein structures from x-ray diffraction data (x-ray crystallography) corresponds to a phase retrieval problem with undersampled amplitude data. Algorithms for this problem...
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ISBN:
(纸本)0819437689
The central problem in the determination of protein structures from x-ray diffraction data (x-ray crystallography) corresponds to a phase retrieval problem with undersampled amplitude data. Algorithms for this problem that have an increased radius of convergence have the potential for reducing the amount of experimental work, and cost, involved in determining protein structures. We describe such an algorithm. Application of the algorithm to a simulated crystallographic problem shows that it converges to the correct solution, with no initial phase information, where currently used algorithms fail. The results lend support to the possibility of ab initio phasing in protein crystallography.
Modern high sensitivity radio interferometric telescopes use ultra wide-band receivers on a large number of antenna elements to achieve the capability of imaging dynamic ranges in excess of 1:1,000,000. In practice, t...
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ISBN:
(纸本)9780819492173
Modern high sensitivity radio interferometric telescopes use ultra wide-band receivers on a large number of antenna elements to achieve the capability of imaging dynamic ranges in excess of 1:1,000,000. In practice, the imaging performance is limited by instrumental and ionospheric/atmospheric effects that corrupt the recorded data. Many of these effects are directionally dependent and vary with time and frequency. Correcting for them is therefore fundamentally more difficult and these effects have been ignored in classical imagereconstruction algorithms. Few attempts in the past to correct for these effects in the image-domain did not deliver the required accuracy. Recent developments in new algorithms that can account for such direction dependent effects show promising results. In this paper I give a general mathematical description of these techniques, show that the resulting algorithms are more optimal in terms of imaging performance and computing requirements and show some results.
Many significant features of images are represented in their Fourier transform. The spectral phase of an image can often be measured more precisely than magnitude for frequencies of up to a few GHz. However, spectral ...
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ISBN:
(纸本)0819445592
Many significant features of images are represented in their Fourier transform. The spectral phase of an image can often be measured more precisely than magnitude for frequencies of up to a few GHz. However, spectral magnitude is the only measurable data in many imaging applications. In this paper, the reconstruction of complex-valued images from either the phases or magnitudes of their Fourier transform is addressed. Conditions for unique representation of a complex-valued image by its spectral magnitude combined with additional spatial information is investigated and presented. reconstruction algorithms of complex-valued images are developed and introduced. Three types of reconstruction algorithms are presented. (1) Algorithms that reconstruct a complex-valued imagefrom the magnitude of its discrete Fourier transform and part of its spatial samples based on the autocorrelation function. (2) Iterative algorithms based on the Gerchberg and Saxton approach. (3) Algorithms that reconstruct a complex-valued imagefrom its localized Fourier transform magnitude. The advantages of the proposed algorithms over the presently available approaches are presented and discussed.
The proceedings contains 22 papers from the SPIE conference on imagereconstructionfromincompletedata II. Topics discussed include: comparison of reconstruction algorithms for images from sparse-aperture systems;im...
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The proceedings contains 22 papers from the SPIE conference on imagereconstructionfromincompletedata II. Topics discussed include: comparison of reconstruction algorithms for images from sparse-aperture systems;imaging fluorescence parameters by Bayesian optical diffusion tomography;blind deconvolution of speckle images constrained by wavefront sensing data;automated target morphing applied to objects in cluttered backgrounds;reconstruction of seismic data using adaptive regularization;and continuous and discrete space particle filters for predictions in acoustic positioning.
Accurate reconstruction of attenuation maps fromincomplete sinograms are required in some cases of SPECT and PET imaging. This paper proposes a new method to directly reconstruct segmented attenuation maps from the i...
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Accurate reconstruction of attenuation maps fromincomplete sinograms are required in some cases of SPECT and PET imaging. This paper proposes a new method to directly reconstruct segmented attenuation maps from the incomplete sinograms. The proposed method is based on an image labeling technique where an optimum label configuration minimizing some energy function is found by using a stochastic sampling with simulated annealing Unlike ordinary image labeling techniques, however, we introduce a powerful constraint called the topology-preserving constraint. This constraint reduces the search space to a set of label configurations having the same topology as the known topology of the attenuation map in question. The experimental results demonstrate that the topology-preserving constraint is powerful enough to reconstruct accurate segmented attenuation aiaps from the incomplete sinograms. The proposed method is tested with simulated data and PET transmission data.
In seismic data processing, we often need to interpolate/extrapolate missing spatial locations in a domain of interest. The reconstruction problem can be posed as an inverse problem where from inadequate and incomplet...
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ISBN:
(纸本)0819445592
In seismic data processing, we often need to interpolate/extrapolate missing spatial locations in a domain of interest. The reconstruction problem can be posed as an inverse problem where from inadequate and incompletedata one attempts to recover the complete band-limited seismic wavefield. However, the problem is often ill posed due to factors such as inaccurate knowledge of bandwidth and noise. In this case, regularization can be used to help to obtain a unique and stable solution. In this paper, we formulate band-limited datareconstruction as a minimum norm least squares type problem where an adaptive DFT-weighted norm regularization term is used to constrain the solution. In particular, the regularization term is iteratively updated through using the modified periodogram of the estimated data. The technique allows for adaptive incorporation of prior knowledge of the data such as the spectrum support and the shape of the spectrum. The adaptive regularization can be accelerated using FFTs and an iterative solver like preconditioned conjugate gradient algorithm. Examples on synthetic and real seismic data illustrate improvement of the new method over damped least squares estimation.
The problem of estimating the wind velocity from measurement of limited flight datafrom a sailplane flight in atmospheric mountain waves is considered. Sailplanes are often equipped with a flight recorder that record...
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ISBN:
(纸本)9780819482969
The problem of estimating the wind velocity from measurement of limited flight datafrom a sailplane flight in atmospheric mountain waves is considered. Sailplanes are often equipped with a flight recorder that records position, and sometimes other information, at regular intervals during the flight. These data contain information on the state of the atmosphere during the flight. A maximum likelihood method is developed for estimating wind fields using such sailplane flight data. The methods are evaluated by application to simulated flight data.
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