The Experts below are selected from a list of 2328 Experts worldwide ranked by ideXlab platform
Ulrich Neitzel - One of the best experts on this subject based on the ideXlab platform.
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accuracy of a simple method for deriving the presampled modulation transfer function of a digital radiographic system from an edge image
Medical Physics, 2003Co-Authors: Egbert Buhr, Susanne Guntherkohfahl, Ulrich NeitzelAbstract:Several methods for accurately deriving the presampled modulation transfer function (MTF) of a pixelated detector from the image of a slightly slanted edge have been described in the literature. In this paper we report on a simple variant of the edge method that produces sufficiently accurate MTF values for frequencies up to the Nyquist frequency Limit of the detector with little effort in edge alignment and computation. The oversampled ESF is constructed in a very simple manner by rearranging the pixel data of N consecutive lines corresponding to a lateral shift of the edge by one pixel. A regular subsampling pitch is assumed for the oversampled ESF, which is given by the original pixel sampling distance divided by the integer number N. This allows the original data to be used for further computational analysis (differentiation and Fourier transform) without data preprocessing. Since the number of lines leading to an edge shift by one pixel generally is a fractional number rather than an integer, a systematic error may be introduced into the presampled MTF. Simulations and theoretical investigations show that this error is proportional to 1/N and increases with spatial frequency. For all frequencies up to the Nyquist Limit, the relative error Δ MTF/MTF is smaller than 1/(2N). It can thus be kept below a given threshold by suitably selecting N, which furnishes a certain maximum edge angle. The method is especially useful for applications where the presampled MTF is needed only for frequencies up to the Nyquist frequency Limit, such as the determination of the detective quantum efficiency (DQE).
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accuracy of a simple method for deriving the presampled modulation transfer function of a digital radiographic system from an edge image
Medical Physics, 2003Co-Authors: Egbert Buhr, Susanne Guntherkohfahl, Ulrich NeitzelAbstract:Several methods for accurately deriving the presampled modulation transfer function (MTF) of a pixelated detector from the image of a slightly slanted edge have been described in the literature. In this paper we report on a simple variant of the edge method that produces sufficiently accurate MTF values for frequencies up to the Nyquist frequency Limit of the detector with little effort in edge alignment and computation. The oversampled ESF is constructed in a very simple manner by rearranging the pixel data of N consecutive lines corresponding to a lateral shift of the edge by one pixel. A regular subsampling pitch is assumed for the oversampled ESF, which is given by the original pixel sampling distance divided by the integer number N. This allows the original data to be used for further computational analysis (differentiation and Fourier transform) without data preprocessing. Since the number of lines leading to an edge shift by one pixel generally is a fractional number rather than an integer, a systematic error may be introduced into the presampled MTF. Simulations and theoretical investigations show that this error is proportional to 1/N and increases with spatial frequency. For all frequencies up to the Nyquist Limit, the relative error delta MTF/MTF is smaller than 1/(2N). It can thus be kept below a given threshold by suitably selecting N, which furnishes a certain maximum edge angle. The method is especially useful for applications where the presampled MTF is needed only for frequencies up to the Nyquist frequency Limit, such as the determination of the detective quantum efficiency (DQE).
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simple method for modulation transfer function determination of digital imaging detectors from edge images
Medical Imaging 2003: Physics of Medical Imaging, 2003Co-Authors: Egbert Buhr, Susanne Guentherkohfahl, Ulrich NeitzelAbstract:A simple variant of the edge method to determine the presampled modulation transfer function (MTF) of digital imaging detectors has been developed that produces sufficiently accurate MTF values for frequencies up to the Nyquist frequency Limit of the detector with only a small amount of effort for alignment and computing. An oversampled edge spread function (ESF) is generated from the image of a slanted edge by rearranging the pixel data of N consecutive lines that correspond to a lateral shift of the edge of one pixel. The original data are used for the computational analysis without further data preprocessing. Since the number of lines leading to an edge shift of one pixel is generally a fractional number rather than an integer, a systematic error may be introduced in the MTF obtained. Simulations and theoretical investigations show that for all frequencies up to the Nyquist Limit the relative error ∆MTF/MTF is below 1/(2N) and can thus be kept below a given threshold by a suitable choice of N. The method is especially useful for applications where the MTF is needed for frequencies up to the Nyquist frequency Limit, like the determination of the detective quantum efficiency (DQE).
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image quality of a digital chest radiography system based on a selenium detector
Medical Physics, 1994Co-Authors: Ulrich Neitzel, Ingo Maack, Susanne GuntherkohfahlAbstract:A digital chest radiographysystem has been developed, with a detector based on the photoelectric properties of amorphous selenium. The selenium layer is deposited on a cylindrical aluminium drum, large enough to cover the full field of view for chest imaging. The electrostatic charge image which is formed on the selenium surface after x‐ray exposure is read out by electrometer probes using fast drum rotation. For a physical evaluation of the attainable image quality, the characteristic curve, the modulation transfer function, and the noise spectra were measured. From these measurements, the signal‐to‐noise properties of the detector in terms of detective quantum efficiency (DQE) and noise equivalent quanta (NEQ) were derived. The results show that the selenium‐based detector has a wide dynamic range and a significantly better DQE than screen‐film and storage phosphor systems for spatial frequencies below the Nyquist Limit (2.7 lp/mm). As a consequence, the detectability of small, low‐contrast details is considerably improved.
Susanne Guntherkohfahl - One of the best experts on this subject based on the ideXlab platform.
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accuracy of a simple method for deriving the presampled modulation transfer function of a digital radiographic system from an edge image
Medical Physics, 2003Co-Authors: Egbert Buhr, Susanne Guntherkohfahl, Ulrich NeitzelAbstract:Several methods for accurately deriving the presampled modulation transfer function (MTF) of a pixelated detector from the image of a slightly slanted edge have been described in the literature. In this paper we report on a simple variant of the edge method that produces sufficiently accurate MTF values for frequencies up to the Nyquist frequency Limit of the detector with little effort in edge alignment and computation. The oversampled ESF is constructed in a very simple manner by rearranging the pixel data of N consecutive lines corresponding to a lateral shift of the edge by one pixel. A regular subsampling pitch is assumed for the oversampled ESF, which is given by the original pixel sampling distance divided by the integer number N. This allows the original data to be used for further computational analysis (differentiation and Fourier transform) without data preprocessing. Since the number of lines leading to an edge shift by one pixel generally is a fractional number rather than an integer, a systematic error may be introduced into the presampled MTF. Simulations and theoretical investigations show that this error is proportional to 1/N and increases with spatial frequency. For all frequencies up to the Nyquist Limit, the relative error delta MTF/MTF is smaller than 1/(2N). It can thus be kept below a given threshold by suitably selecting N, which furnishes a certain maximum edge angle. The method is especially useful for applications where the presampled MTF is needed only for frequencies up to the Nyquist frequency Limit, such as the determination of the detective quantum efficiency (DQE).
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accuracy of a simple method for deriving the presampled modulation transfer function of a digital radiographic system from an edge image
Medical Physics, 2003Co-Authors: Egbert Buhr, Susanne Guntherkohfahl, Ulrich NeitzelAbstract:Several methods for accurately deriving the presampled modulation transfer function (MTF) of a pixelated detector from the image of a slightly slanted edge have been described in the literature. In this paper we report on a simple variant of the edge method that produces sufficiently accurate MTF values for frequencies up to the Nyquist frequency Limit of the detector with little effort in edge alignment and computation. The oversampled ESF is constructed in a very simple manner by rearranging the pixel data of N consecutive lines corresponding to a lateral shift of the edge by one pixel. A regular subsampling pitch is assumed for the oversampled ESF, which is given by the original pixel sampling distance divided by the integer number N. This allows the original data to be used for further computational analysis (differentiation and Fourier transform) without data preprocessing. Since the number of lines leading to an edge shift by one pixel generally is a fractional number rather than an integer, a systematic error may be introduced into the presampled MTF. Simulations and theoretical investigations show that this error is proportional to 1/N and increases with spatial frequency. For all frequencies up to the Nyquist Limit, the relative error Δ MTF/MTF is smaller than 1/(2N). It can thus be kept below a given threshold by suitably selecting N, which furnishes a certain maximum edge angle. The method is especially useful for applications where the presampled MTF is needed only for frequencies up to the Nyquist frequency Limit, such as the determination of the detective quantum efficiency (DQE).
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image quality of a digital chest radiography system based on a selenium detector
Medical Physics, 1994Co-Authors: Ulrich Neitzel, Ingo Maack, Susanne GuntherkohfahlAbstract:A digital chest radiographysystem has been developed, with a detector based on the photoelectric properties of amorphous selenium. The selenium layer is deposited on a cylindrical aluminium drum, large enough to cover the full field of view for chest imaging. The electrostatic charge image which is formed on the selenium surface after x‐ray exposure is read out by electrometer probes using fast drum rotation. For a physical evaluation of the attainable image quality, the characteristic curve, the modulation transfer function, and the noise spectra were measured. From these measurements, the signal‐to‐noise properties of the detector in terms of detective quantum efficiency (DQE) and noise equivalent quanta (NEQ) were derived. The results show that the selenium‐based detector has a wide dynamic range and a significantly better DQE than screen‐film and storage phosphor systems for spatial frequencies below the Nyquist Limit (2.7 lp/mm). As a consequence, the detectability of small, low‐contrast details is considerably improved.
Johannes F. De Boer - One of the best experts on this subject based on the ideXlab platform.
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Ultimate resolution Limits of speckle-based compressive imaging.
Optics express, 2021Co-Authors: Benjamin Lochocki, Johannes F. De Boer, K. A. Abrashitova, Lyubov V. AmitonovaAbstract:Compressive imaging using sparsity constraints is a very promising field of microscopy that provides a dramatic enhancement of the spatial resolution beyond the Abbe diffraction Limit. Moreover, it simultaneously overcomes the Nyquist Limit by reconstructing an N-pixel image from less than N single-point measurements. Here we present fundamental resolution Limits of noiseless compressive imaging via sparsity constraints, speckle illumination and single-pixel detection. We addressed the experimental setup that uses randomly generated speckle patterns (in a scattering media or a multimode fiber). The optimal number of measurements, the ultimate spatial resolution Limit and the surprisingly important role of discretization are demonstrated by the theoretical analysis and numerical simulations. We show that, in contrast to conventional microscopy, oversampling may decrease the resolution and reconstruction quality of compressive imaging.
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Endo-microscopy beyond the Abbe and Nyquist Limits
Light science & applications, 2020Co-Authors: Lyubov V. Amitonova, Johannes F. De BoerAbstract:For several centuries, far-field optical microscopy has remained a key instrument in many scientific disciplines, including physical, chemical, and biomedical research. Nonetheless, far-field imaging has many Limitations: the spatial resolution is controlled by the diffraction of light, and the imaging speed follows the Nyquist-Shannon sampling theorem. The recent development of super-resolution techniques has pushed the Limits of spatial resolution. However, these methods typically require complicated setups and long acquisition times and are still not applicable to deep-tissue bioimaging. Here, we report imaging through an ultra-thin fibre probe with a spatial resolution beyond the Abbe Limit and a temporal resolution beyond the Nyquist Limit simultaneously in a simple and compact setup. We use the random nature of mode coupling in a multimode fibre, the sparsity constraint and compressive sensing reconstruction. The new approach of super-resolution endo-microscopy does not use any specific properties of the fluorescent label, such as depletion or stochastic activation of the molecular fluorescent state, and therefore can be used for label-free imaging. We demonstrate a spatial resolution more than 2 times better than the diffraction Limit and an imaging speed 20 times faster than the Nyquist Limit. The proposed approach can significantly expand the realm of the application of nanoscopy for bioimaging.
Lyubov V. Amitonova - One of the best experts on this subject based on the ideXlab platform.
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Ultimate resolution Limits of speckle-based compressive imaging.
Optics express, 2021Co-Authors: Benjamin Lochocki, Johannes F. De Boer, K. A. Abrashitova, Lyubov V. AmitonovaAbstract:Compressive imaging using sparsity constraints is a very promising field of microscopy that provides a dramatic enhancement of the spatial resolution beyond the Abbe diffraction Limit. Moreover, it simultaneously overcomes the Nyquist Limit by reconstructing an N-pixel image from less than N single-point measurements. Here we present fundamental resolution Limits of noiseless compressive imaging via sparsity constraints, speckle illumination and single-pixel detection. We addressed the experimental setup that uses randomly generated speckle patterns (in a scattering media or a multimode fiber). The optimal number of measurements, the ultimate spatial resolution Limit and the surprisingly important role of discretization are demonstrated by the theoretical analysis and numerical simulations. We show that, in contrast to conventional microscopy, oversampling may decrease the resolution and reconstruction quality of compressive imaging.
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Endo-microscopy beyond the Abbe and Nyquist Limits
Light science & applications, 2020Co-Authors: Lyubov V. Amitonova, Johannes F. De BoerAbstract:For several centuries, far-field optical microscopy has remained a key instrument in many scientific disciplines, including physical, chemical, and biomedical research. Nonetheless, far-field imaging has many Limitations: the spatial resolution is controlled by the diffraction of light, and the imaging speed follows the Nyquist-Shannon sampling theorem. The recent development of super-resolution techniques has pushed the Limits of spatial resolution. However, these methods typically require complicated setups and long acquisition times and are still not applicable to deep-tissue bioimaging. Here, we report imaging through an ultra-thin fibre probe with a spatial resolution beyond the Abbe Limit and a temporal resolution beyond the Nyquist Limit simultaneously in a simple and compact setup. We use the random nature of mode coupling in a multimode fibre, the sparsity constraint and compressive sensing reconstruction. The new approach of super-resolution endo-microscopy does not use any specific properties of the fluorescent label, such as depletion or stochastic activation of the molecular fluorescent state, and therefore can be used for label-free imaging. We demonstrate a spatial resolution more than 2 times better than the diffraction Limit and an imaging speed 20 times faster than the Nyquist Limit. The proposed approach can significantly expand the realm of the application of nanoscopy for bioimaging.
Kiryung Lee - One of the best experts on this subject based on the ideXlab platform.
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compressive sampling using annihilating filter based low rank interpolation
IEEE Transactions on Information Theory, 2017Co-Authors: Jong Min Kim, Kyong Hwan Jin, Kiryung LeeAbstract:While the recent theory of compressed sensing provides an opportunity to overcome the Nyquist Limit in recovering sparse signals, a solution approach usually takes the form of an inverse problem of an unknown signal, which is crucially dependent on specific signal representation. In this paper, we propose a drastically different two-step Fourier compressive sampling framework in a continuous domain that can be implemented via measurement domain interpolation, after which signal reconstruction can be done using classical analytic reconstruction methods. The main idea originates from the fundamental duality between the sparsity in the primary space and the low-rankness of a structured matrix in the spectral domain, showing that a low-rank interpolator in the spectral domain can enjoy all of the benefits of sparse recovery with performance guarantees. Most notably, the proposed low-rank interpolation approach can be regarded as a generalization of recent spectral compressed sensing to recover large classes of finite rate of innovations (FRI) signals at a near-optimal sampling rate. Moreover, for the case of cardinal representation, we can show that the proposed low-rank interpolation scheme will benefit from inherent regularization and an optimal incoherence parameter. Using a powerful dual certificate and the golfing scheme, we show that the new framework still achieves a near-optimal sampling rate for a general class of FRI signal recovery, while the sampling rate can be further reduced for a class of cardinal splines. Numerical results using various types of FRI signals confirm that the proposed low-rank interpolation approach offers significantly better phase transitions than conventional compressive sampling approaches.
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compressive sampling using annihilating filter based low rank interpolation
arXiv: Information Theory, 2015Co-Authors: Jong Min Kim, Kyong Hwan Jin, Kiryung LeeAbstract:While the recent theory of compressed sensing provides an opportunity to overcome the Nyquist Limit in recovering sparse signals, a solution approach usually takes a form of inverse problem of the unknown signal, which is crucially dependent on specific signal representation. In this paper, we propose a drastically different two-step Fourier compressive sampling framework in continuous domain that can be implemented as a measurement domain interpolation, after which a signal reconstruction can be done using classical analytic reconstruction methods. The main idea is originated from the fundamental duality between the sparsity in the primary space and the low-rankness of a structured matrix in the spectral domain, which shows that a low-rank interpolator in the spectral domain can enjoy all the benefit of sparse recovery with performance guarantees. Most notably, the proposed low-rank interpolation approach can be regarded as a generalization of recent spectral compressed sensing to recover large class of finite rate of innovations (FRI) signals at near optimal sampling rate. Moreover, for the case of cardinal representation, we can show that the proposed low-rank interpolation will benefit from inherent regularization and the optimal incoherence parameter. Using the powerful dual certificates and golfing scheme, we show that the new framework still achieves the near-optimal sampling rate for general class of FRI signal recovery, and the sampling rate can be further reduced for the class of cardinal splines. Numerical results using various type of FRI signals confirmed that the proposed low-rank interpolation approach has significant better phase transition than the conventional CS approaches.