Coded apertures for x-ray scatter imaging

We examine coding strategies for coded aperture scatter imagers. Scatter imaging enables tomography of compact regions from snapshot measurements. We present coded aperture designs for pencil and fan beam geometries, and compare their singular value spectra with that of the Radon transform and selected volume tomography.We show that under dose constraints scatter imaging improves conditioning over alternative techniques, and that specially designed coded apertures enable snapshot 1D and 2

Dosimetric impact of range uncertainty in passive scattering proton therapy

PURPOSE: The objective of this study was to investigate the dosimetric impact of range uncertainty in a large cohort of patients receiving passive scatter proton therapy. METHODS: A cohort of 120 patients were reviewed in this study retrospectively, of which 61 were brain, 39 lung, and 20 prostate patients. Range uncertainties of ±3.5% (overshooting and undershooting by 3.5%, respectively) were added and recalculated on the original plans, which had been planned according to our clinical planning protocol while keeping beamlines, apertures, compensators, and dose grids intact. Changes in the coverage on CTV and DVH for critical organs were compared and analyzed. Correlation between dose change and minimal distance between CTV and critical organs were also investigated. RESULTS: Although CTV coverages and maximum dose to critical organs were largely maintained for most brain patients, large variations over 5% were still observed sporadically. Critical organs, such as brainstem and chiasm, could still be affected by range uncertainty at 4 cm away from CTV. Coverage and OARs in lung and prostate patients were less likely to be affected by range uncertainty with very few exceptions. CONCLUSION: The margin recipe in modern TPS leads to clinically acceptable OAR doses in the presence of range uncertainties. However, range uncertainties still pose a noticeable challenge for small but critical serial organs near tumors, and occasionally for large parallel organs that are located distal to incident proton beams

Computational hyperspectral interferometry for studies of brain function: Proof of concept

Hyperspectral interferometric microscopy uses a unique combination of optics and algorithm design to extract information. Local brain activity rapidly changes local blood flow and red blood cell concentration (absorption) and oxygenation (color). We demonstrate that brain activity evoked during whisker stimulation can be detected with hyperspectral interferometric microscopy to identify the active whisker-barrel cortex in the rat brain. Information about constituent components is extracted across the entire spectral band. Algorithms can be flexibly optimized to discover, detect, quantify, and visualize a wide range of significant biological events, including changes relevant to the diagnosis and treatment of disease. © 2006 Optical Society of America

Theoretical Analysis of Quantum Ghost Imaging Through Turbulence

Atmospheric turbulence generally affects the resolution and visibility of an image in long-distance imaging. In a recent quantum ghost imaging experiment [P. B. Dixon et al., Phys. Rev. A 83, 051803 (2011)], it was found that the effect of the turbulence can nevertheless be mitigated under certain conditions. This paper gives a detailed theoretical analysis to the setup and results reported in the experiment. Entangled photons with a finite correlation area and a turbulence model beyond the phase screen approximation are considered

Implementation and evaluation of a penalized alternating minimization algorithm for computational DIC microscopy

We present the implementation and evaluation of a penalized alternating minimization (AM) method for the computation of a specimen\u27s complex transmittance function (magnitude and phase) from images captured with Differential Interference Contrast (DIC) microscopy. The magnitude of the transmittance function is constrained to be less than 1. The penalty is on the roughness of the complex transmittance function. Without the penalty, we show via simulation that the difference between the true and estimated transmittance function takes values in the null space of the DIC point-spread function, thereby characterizing the ill-posed nature of this inverse problem. The penalty effectively attenuates larger spatial frequencies that are in this null space. The algorithm is implemented on yeast cell images after proper normalization of the measured data. Preliminary results are promising. © 2010 Copyright SPIE - The International Society for Optical Engineering

Computational differential interference contrast (DIC) microscopy for quantitative imaging

We demonstrate that application of a regularized alternating minimization algorithm to DIC microscopy images results in quantitative imaging of the specimen\u27s phase and amplitude information. The alternating minimization algorithm\u27s robustness to noise is investigated. © 2009 Optical Society of America

Quantitative determination of specimen properties using computational differential-interference contrast (DIC) microscopy

The theoretical development of a new iterative method based on a diffraction imaging model for the computation of a specimen\u27s complex transmittance function (magnitude and phase) from DIC images is presented. This new method extends our initial work (RD method presented by Preza1) which was based on the assumption that the specimen does not absorb light and thus only the specimen\u27s phase function or optical path length (OPL) distribution was computed from rotationally-diverse (RD) DIC images. In this paper, we quantify this approximation by modeling the magnitude of the synthetic object as a deviation from unity by a small perturbation. Synthetic, noiseless DIC data are generated from these test objects and processed with the RD method. Our results show that although for weakly absorbing objects the RD method may be adequate for some applications, in general the results can be quantitatively unacceptable. This supports the development of the new alternating minimization method presented in this paper. Preliminary results from the current implementation of the AM method show that the discrepancy measure utilized in the method goes to zero as iterations increase but a constrain on the estimated magnitude is necessary in order to obtain quantitative specimen properties. © 2007 SPIE-OSA

Spectrum Estimation from Quantum-Limited Interferograms

A quantitative model for interferogram data collected in a quantum-limited hyperspectral imaging system is derived. This model accounts for the geometry of the interferometer, the Poisson noise, and the parameterization of the mean of the noise in terms of the autocorrelation function of the incident optical signal. The Cramér-Rao bound on the variance of unbiased spectrum estimates is derived and provides an explanation for what is often called the multiplex disadvantage in interferometer-based methods. Three spectrum estimation algorithms are studied: maximum likelihood via the expectation-maximization (EM) algorithm, least squares (LS), and the fast Fourier transform (FFT) with data precorrection. Extensive simulation results reveal advantages and disadvantages with all three methods in different signal-to-noise ratio (SNR) regimes