X-ray tomography is a non-destructive imaging technique that reveals the interior of an object fr... more X-ray tomography is a non-destructive imaging technique that reveals the interior of an object from its projections at different angles. Under sparse-view and low-photon sampling, regularization priors are required to retrieve a high-fidelity reconstruction. Recently, deep learning has been used in X-ray tomography. The prior learned from training data replaces the general-purpose priors in iterative algorithms, achieving high-quality reconstructions with a neural network. Previous studies typically assume the noise statistics of testing data is acquired a priori from training data, leaving the network susceptible to a change in the noise characteristics under practical imaging conditions. In this work, we propose a noise-resilient deep-reconstruction algorithm for X-ray tomography. By training the network with regularized reconstructions from a conventional algorithm, the learned prior shows strong noise resilience without the need for additional training with noisy examples, and a...
Face masks do not completely prevent transmission of respiratory infections, but masked individua... more Face masks do not completely prevent transmission of respiratory infections, but masked individuals are likely to inhale fewer infectious particles. If smaller infectious doses tend to yield milder infections, yet ultimately induce similar levels of immunity, then masking could reduce the prevalence of severe disease even if the total number of infections is unaffected. It has been suggested that this effect of masking is analogous to the pre-vaccination practice of variolation for smallpox, whereby susceptible individuals were intentionally infected with small doses of live virus (and often acquired immunity without severe disease). We present a simple epidemiological model in which mask-induced variolation causes milder infections, potentially with lower transmission rate and/or different duration. We derive relationships between the effectiveness of mask-induced variolation and important epidemiological metrics (the basic reproduction number and initial epidemic growth rate, and ...
X-ray tomography is capable of imaging the interior of objects in three dimensions non-invasively... more X-ray tomography is capable of imaging the interior of objects in three dimensions non-invasively, with applications in biomedical imaging, materials science, electronic inspection, and other fields. The reconstruction process can be an ill-conditioned inverse problem, requiring regularization to obtain satisfactory results. Recently, deep learning has been adopted for tomographic reconstruction. Unlike iterative algorithms which require a distribution that is known a priori, deep reconstruction networks can learn a prior distribution through sampling the training distributions. In this work, we develop a Physics-assisted Generative Adversarial Network (PGAN), a two-step algorithm for tomographic reconstruction. In contrast to previous efforts, our PGAN utilizes maximum-likelihood estimates derived from the measurements to regularize the reconstruction with both known physics and the learned prior. Compared with methods with less physics assisting in training, PGAN can reduce the ph...
C++ code for Monte Carlo calculation of optical scattering in multi-layer material. Described in ... more C++ code for Monte Carlo calculation of optical scattering in multi-layer material. Described in RH Streater, A-MR Lieberson, AL Pintar. and ZH Levine, "A parallel version of MCML and an Inverse Monte Carlo Algorithm to Calculate Optical Scattering Parameters," J. Res. NIST, https://doi.org/10.6028/jresnist.122.038. See also the main article RH Streater, A-MR Lieberson, AL Pintar, CC Cooksey, and P Lemaillet, unpublished.
Data will be posted here to allow re-analysis of published work. Typical CT data sets are up to 1... more Data will be posted here to allow re-analysis of published work. Typical CT data sets are up to 1 gigabyte in size. Medical CT yields data in DICOM format.
DICOM files are given for 11 CT scans which were used in a research article. Each scan contains a... more DICOM files are given for 11 CT scans which were used in a research article. Each scan contains about 1250 slices with 512x512 gray scale images, each in its own directory. The low number slices contain the diapers in the order D5 ... D1, then the vials of powder are contained in the order V11 ... V2. The symbols correspond to the injected masses which are given in the paper and which are repeated here in a file called "mass.txt". There is also a file "README.txt" which describes the directory structure.
The data is for the companion paper: ZH Levine et al., The detection of carbon dioxide leaks usin... more The data is for the companion paper: ZH Levine et al., The detection of carbon dioxide leaks using quasi-tomographic laser absorption spectroscopy, Atmospheric Measurement Techniques, in press (to appear 2016). The data include measurements carbon dioxide in the atmosphere in a field in Ft. Wayne, Indiana as well as simulations of such measurements.
Coherent states are used to prepare a crystal using the Atomic Frequency Comb protocol for quantu... more Coherent states are used to prepare a crystal using the Atomic Frequency Comb protocol for quantum memory. Here, semiclassical theory is developed and compared to experimental photon echoes of a coherent pulse.
Praseodymium-doped yttrium orthosilicate prepared by an optical frequency comb is a candidate for... more Praseodymium-doped yttrium orthosilicate prepared by an optical frequency comb is a candidate for quantum memory, although its hyperfine splitting poses challenges. Transmission after preparation is predicted using the density matrix.
Lecture Notes in Economics and Mathematical Systems, 1973
Inductive reasoning relies on a limited data base, say R, to produce hopefully universally true s... more Inductive reasoning relies on a limited data base, say R, to produce hopefully universally true statements expressed as hypotheses, say li. In decision making, control is sought over certain events that are affected by some variable(s) or by some relation(s). The hypotheses concern the values of these variables and the structure of these relations. As P6lya has formulated it, the inductive infer-T. Einsele et al.
RECIST (Response Evaluation Criteria in Solid Tumors) is a linear 13 measure intended to predict ... more RECIST (Response Evaluation Criteria in Solid Tumors) is a linear 13 measure intended to predict tumor volume in medical computed tomography 14 (CT). In this work, using purely geometrical considerations, we estimate how 15 well RECIST can predict the volume of randomly-oriented tumor models, each 16 composed of the union of ellipsoids. The principal conclusion is that RECIST is 17 likely to work less well for realistic tumors than for ellipsoids. 18
X-ray tomography is a non-destructive imaging technique that reveals the interior of an object fr... more X-ray tomography is a non-destructive imaging technique that reveals the interior of an object from its projections at different angles. Under sparse-view and low-photon sampling, regularization priors are required to retrieve a high-fidelity reconstruction. Recently, deep learning has been used in X-ray tomography. The prior learned from training data replaces the general-purpose priors in iterative algorithms, achieving high-quality reconstructions with a neural network. Previous studies typically assume the noise statistics of testing data is acquired a priori from training data, leaving the network susceptible to a change in the noise characteristics under practical imaging conditions. In this work, we propose a noise-resilient deep-reconstruction algorithm for X-ray tomography. By training the network with regularized reconstructions from a conventional algorithm, the learned prior shows strong noise resilience without the need for additional training with noisy examples, and a...
Face masks do not completely prevent transmission of respiratory infections, but masked individua... more Face masks do not completely prevent transmission of respiratory infections, but masked individuals are likely to inhale fewer infectious particles. If smaller infectious doses tend to yield milder infections, yet ultimately induce similar levels of immunity, then masking could reduce the prevalence of severe disease even if the total number of infections is unaffected. It has been suggested that this effect of masking is analogous to the pre-vaccination practice of variolation for smallpox, whereby susceptible individuals were intentionally infected with small doses of live virus (and often acquired immunity without severe disease). We present a simple epidemiological model in which mask-induced variolation causes milder infections, potentially with lower transmission rate and/or different duration. We derive relationships between the effectiveness of mask-induced variolation and important epidemiological metrics (the basic reproduction number and initial epidemic growth rate, and ...
X-ray tomography is capable of imaging the interior of objects in three dimensions non-invasively... more X-ray tomography is capable of imaging the interior of objects in three dimensions non-invasively, with applications in biomedical imaging, materials science, electronic inspection, and other fields. The reconstruction process can be an ill-conditioned inverse problem, requiring regularization to obtain satisfactory results. Recently, deep learning has been adopted for tomographic reconstruction. Unlike iterative algorithms which require a distribution that is known a priori, deep reconstruction networks can learn a prior distribution through sampling the training distributions. In this work, we develop a Physics-assisted Generative Adversarial Network (PGAN), a two-step algorithm for tomographic reconstruction. In contrast to previous efforts, our PGAN utilizes maximum-likelihood estimates derived from the measurements to regularize the reconstruction with both known physics and the learned prior. Compared with methods with less physics assisting in training, PGAN can reduce the ph...
C++ code for Monte Carlo calculation of optical scattering in multi-layer material. Described in ... more C++ code for Monte Carlo calculation of optical scattering in multi-layer material. Described in RH Streater, A-MR Lieberson, AL Pintar. and ZH Levine, "A parallel version of MCML and an Inverse Monte Carlo Algorithm to Calculate Optical Scattering Parameters," J. Res. NIST, https://doi.org/10.6028/jresnist.122.038. See also the main article RH Streater, A-MR Lieberson, AL Pintar, CC Cooksey, and P Lemaillet, unpublished.
Data will be posted here to allow re-analysis of published work. Typical CT data sets are up to 1... more Data will be posted here to allow re-analysis of published work. Typical CT data sets are up to 1 gigabyte in size. Medical CT yields data in DICOM format.
DICOM files are given for 11 CT scans which were used in a research article. Each scan contains a... more DICOM files are given for 11 CT scans which were used in a research article. Each scan contains about 1250 slices with 512x512 gray scale images, each in its own directory. The low number slices contain the diapers in the order D5 ... D1, then the vials of powder are contained in the order V11 ... V2. The symbols correspond to the injected masses which are given in the paper and which are repeated here in a file called "mass.txt". There is also a file "README.txt" which describes the directory structure.
The data is for the companion paper: ZH Levine et al., The detection of carbon dioxide leaks usin... more The data is for the companion paper: ZH Levine et al., The detection of carbon dioxide leaks using quasi-tomographic laser absorption spectroscopy, Atmospheric Measurement Techniques, in press (to appear 2016). The data include measurements carbon dioxide in the atmosphere in a field in Ft. Wayne, Indiana as well as simulations of such measurements.
Coherent states are used to prepare a crystal using the Atomic Frequency Comb protocol for quantu... more Coherent states are used to prepare a crystal using the Atomic Frequency Comb protocol for quantum memory. Here, semiclassical theory is developed and compared to experimental photon echoes of a coherent pulse.
Praseodymium-doped yttrium orthosilicate prepared by an optical frequency comb is a candidate for... more Praseodymium-doped yttrium orthosilicate prepared by an optical frequency comb is a candidate for quantum memory, although its hyperfine splitting poses challenges. Transmission after preparation is predicted using the density matrix.
Lecture Notes in Economics and Mathematical Systems, 1973
Inductive reasoning relies on a limited data base, say R, to produce hopefully universally true s... more Inductive reasoning relies on a limited data base, say R, to produce hopefully universally true statements expressed as hypotheses, say li. In decision making, control is sought over certain events that are affected by some variable(s) or by some relation(s). The hypotheses concern the values of these variables and the structure of these relations. As P6lya has formulated it, the inductive infer-T. Einsele et al.
RECIST (Response Evaluation Criteria in Solid Tumors) is a linear 13 measure intended to predict ... more RECIST (Response Evaluation Criteria in Solid Tumors) is a linear 13 measure intended to predict tumor volume in medical computed tomography 14 (CT). In this work, using purely geometrical considerations, we estimate how 15 well RECIST can predict the volume of randomly-oriented tumor models, each 16 composed of the union of ellipsoids. The principal conclusion is that RECIST is 17 likely to work less well for realistic tumors than for ellipsoids. 18
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Papers by Zachary Levine