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  1. AU="Marchesini, Stefano"
  2. AU=Sgaliny Aude I.
  3. AU="Parker, C C"
  4. AU="Okpala, Ejike Onwudiegwu"

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  1. Article ; Online: Ring artifact and Poisson noise attenuation via volumetric multiscale nonlocal collaborative filtering of spatially correlated noise.

    Mäkinen, Ymir / Marchesini, Stefano / Foi, Alessandro

    Journal of synchrotron radiation

    2022  Volume 29, Issue Pt 3, Page(s) 829–842

    Abstract: X-ray micro-tomography systems often suffer from high levels of noise. In particular, severe ring artifacts are common in reconstructed images, caused by defects in the detector, calibration errors, and fluctuations producing streak noise in the raw ... ...

    Abstract X-ray micro-tomography systems often suffer from high levels of noise. In particular, severe ring artifacts are common in reconstructed images, caused by defects in the detector, calibration errors, and fluctuations producing streak noise in the raw sinogram data. Furthermore, the projections commonly contain high levels of Poissonian noise arising from the photon-counting detector. This work presents a 3-D multiscale framework for streak attenuation through a purposely designed collaborative filtering of correlated noise in volumetric data. A distinct multiscale denoising step for attenuation of the Poissonian noise is further proposed. By utilizing the volumetric structure of the projection data, the proposed fully automatic procedure offers improved feature preservation compared with 2-D denoising and avoids artifacts which arise from individual filtering of sinograms.
    Language English
    Publishing date 2022-04-21
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2021413-3
    ISSN 1600-5775 ; 0909-0495
    ISSN (online) 1600-5775
    ISSN 0909-0495
    DOI 10.1107/S1600577522002739
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Ring artifact reduction via multiscale nonlocal collaborative filtering of spatially correlated noise.

    Mäkinen, Ymir / Marchesini, Stefano / Foi, Alessandro

    Journal of synchrotron radiation

    2021  Volume 28, Issue Pt 3, Page(s) 876–888

    Abstract: X-ray micro-tomography systems often suffer severe ring artifacts in reconstructed images. These artifacts are caused by defects in the detector, calibration errors, and fluctuations producing streak noise in the raw sinogram data. In this work, these ... ...

    Abstract X-ray micro-tomography systems often suffer severe ring artifacts in reconstructed images. These artifacts are caused by defects in the detector, calibration errors, and fluctuations producing streak noise in the raw sinogram data. In this work, these streaks are modeled in the sinogram domain as additive stationary correlated noise upon logarithmic transformation. Based on this model, a streak removal procedure is proposed where the Block-Matching and 3-D (BM3D) filtering algorithm is applied across multiple scales, achieving state-of-the-art performance in both real and simulated data. Specifically, the proposed fully automatic procedure allows for attenuation of streak noise and the corresponding ring artifacts without creating major distortions common to other streak removal algorithms.
    Language English
    Publishing date 2021-04-16
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2021413-3
    ISSN 1600-5775 ; 0909-0495
    ISSN (online) 1600-5775
    ISSN 0909-0495
    DOI 10.1107/S1600577521001910
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Shaping coherent x-rays with binary optics.

    Marchesini, Stefano / Sakdinawat, Anne

    Optics express

    2018  Volume 27, Issue 2, Page(s) 907–917

    Abstract: Diffractive lenses fabricated by lithographic methods are one of the most popular image forming optics in the x-ray regime. Most commonly, binary diffractive optics, such as Fresnel zone plates, are used due to their ability to focus at high resolution ... ...

    Abstract Diffractive lenses fabricated by lithographic methods are one of the most popular image forming optics in the x-ray regime. Most commonly, binary diffractive optics, such as Fresnel zone plates, are used due to their ability to focus at high resolution and to manipulate the x-ray wavefront. We report here a binary zone plate design strategy to form arbitrary illuminations for coherent multiplexing, structured illumination, and wavefront shaping experiments. Given a desired illumination, we adjust the duty cycle, harmonic order, and zone placement to vary both the amplitude and phase of the wavefront at the lens. This enables the binary lithographic pattern to generate arbitrary structured illumination optimized for a variety of applications such as holography, interferometry, ptychography, imaging, and others.
    Language English
    Publishing date 2018-11-15
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1491859-6
    ISSN 1094-4087 ; 1094-4087
    ISSN (online) 1094-4087
    ISSN 1094-4087
    DOI 10.1364/OE.27.000907
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Denoising Poisson phaseless measurements via orthogonal dictionary learning.

    Chang, Huibin / Marchesini, Stefano

    Optics express

    2018  Volume 26, Issue 16, Page(s) 19773–19796

    Abstract: Phaseless diffraction measurements recorded by CCD detectors are often affected by Poisson noise. In this paper, we propose a dictionary learning model by employing patches based sparsity in order to denoise such Poisson phaseless measurements. The model ...

    Abstract Phaseless diffraction measurements recorded by CCD detectors are often affected by Poisson noise. In this paper, we propose a dictionary learning model by employing patches based sparsity in order to denoise such Poisson phaseless measurements. The model consists of three terms: (i) A representation term by an orthogonal dictionary, (ii) an L
    Language English
    Publishing date 2018-08-16
    Publishing country United States
    Document type Journal Article
    ZDB-ID 1491859-6
    ISSN 1094-4087 ; 1094-4087
    ISSN (online) 1094-4087
    ISSN 1094-4087
    DOI 10.1364/OE.26.019773
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article: Iterative X-ray spectroscopic ptychography.

    Chang, Huibin / Rong, Ziqin / Enfedaque, Pablo / Marchesini, Stefano

    Journal of applied crystallography

    2020  Volume 53, Issue Pt 4, Page(s) 937–948

    Abstract: Spectroscopic ptychography is a powerful technique to determine the chemical composition of a sample with high spatial resolution. In spectro-ptychography, a sample is rastered through a focused X-ray beam with varying photon energy so that a series of ... ...

    Abstract Spectroscopic ptychography is a powerful technique to determine the chemical composition of a sample with high spatial resolution. In spectro-ptychography, a sample is rastered through a focused X-ray beam with varying photon energy so that a series of phaseless diffraction data are recorded. Each chemical component in the material under investigation has a characteristic absorption and phase contrast as a function of photon energy. Using a dictionary formed by the set of contrast functions of each energy for each chemical component, it is possible to obtain the chemical composition of the material from high-resolution multi-spectral images. This paper presents SPA (spectroscopic ptychography with alternating direction method of multipliers), a novel algorithm to iteratively solve the spectroscopic blind ptychography problem. First, a nonlinear spectro-ptychography model based on Poisson maximum likelihood is designed, and then the proposed method is constructed on the basis of fast iterative splitting operators. SPA can be used to retrieve spectral contrast when considering either a known or an incomplete (partially known) dictionary of reference spectra. By coupling the redundancy across different spectral measurements, the proposed algorithm can achieve higher reconstruction quality when compared with standard state-of-the-art two-step methods. It is demonstrated how SPA can recover accurate chemical maps from Poisson-noised measurements, and its enhanced robustness when reconstructing reduced-redundancy ptychography data using large scanning step sizes is shown.
    Language English
    Publishing date 2020-07-08
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2020879-0
    ISSN 1600-5767 ; 0021-8898
    ISSN (online) 1600-5767
    ISSN 0021-8898
    DOI 10.1107/S1600576720006354
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: Phase retrieval and saddle-point optimization.

    Marchesini, Stefano

    Journal of the Optical Society of America. A, Optics, image science, and vision

    2007  Volume 24, Issue 10, Page(s) 3289–3296

    Abstract: Iterative algorithms with feedback are among the most powerful and versatile optimization methods for phase retrieval. Among these, the hybrid input-output algorithm has demonstrated practical solutions to giga-element nonlinear phase retrieval problems, ...

    Abstract Iterative algorithms with feedback are among the most powerful and versatile optimization methods for phase retrieval. Among these, the hybrid input-output algorithm has demonstrated practical solutions to giga-element nonlinear phase retrieval problems, escaping local minima and producing images at resolutions beyond the capabilities of lens-based optical methods. Here the input-output iteration is improved by a lower-dimensional subspace saddle-point optimization.
    Language English
    Publishing date 2007-09-01
    Publishing country United States
    Document type Journal Article
    ZDB-ID 283633-6
    ISSN 1520-8532 ; 1084-7529 ; 0740-3232
    ISSN (online) 1520-8532
    ISSN 1084-7529 ; 0740-3232
    DOI 10.1364/josaa.24.003289
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.B 2689: Show issues Location:
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    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

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  7. Article ; Online: Partially coherent ptychography by gradient decomposition of the probe.

    Chang, Huibin / Enfedaque, Pablo / Lou, Yifei / Marchesini, Stefano

    Acta crystallographica. Section A, Foundations and advances

    2018  Volume 74, Issue Pt 3, Page(s) 157–169

    Abstract: Coherent ptychographic imaging experiments often discard the majority of the flux from a light source to define the coherence of the illumination. Even when the coherent flux is sufficient, the stability required during an exposure is another important ... ...

    Abstract Coherent ptychographic imaging experiments often discard the majority of the flux from a light source to define the coherence of the illumination. Even when the coherent flux is sufficient, the stability required during an exposure is another important limiting factor. Partial coherence analysis can considerably reduce these limitations. A partially coherent illumination can often be written as the superposition of a single coherent illumination convolved with a separable translational kernel. This article proposes the gradient decomposition of the probe (GDP), a model that exploits translational kernel separability, coupling the variances of the kernel with the transverse coherence. An efficient first-order splitting algorithm (GDP-ADMM) for solving the proposed nonlinear optimization problem is described. Numerical experiments demonstrate the effectiveness of the proposed method with Gaussian and binary kernel functions in fly-scan measurements. Remarkably, GDP-ADMM using nanoprobes produces satisfactory results even when the ratio between the kernel width and the beam size is more than one, or when the distance between successive acquisitions is twice as large as the beam width.
    Language English
    Publishing date 2018-05-01
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2020844-3
    ISSN 2053-2733 ; 1600-5724 ; 0108-7673
    ISSN (online) 2053-2733 ; 1600-5724
    ISSN 0108-7673
    DOI 10.1107/S2053273318001924
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Book ; Online: Iterative X-ray Spectroscopic Ptychography

    Chang, Huibin / Rong, Ziqin / Enfedaque, Pablo / Marchesini, Stefano

    2019  

    Abstract: Spectroscopic ptychography is a powerful technique to determine the chemical composition of a sample with high spatial resolution. In spectro-ptychography, a sample is rastered through a focused x-ray beam with varying photon energy so that a series of ... ...

    Abstract Spectroscopic ptychography is a powerful technique to determine the chemical composition of a sample with high spatial resolution. In spectro-ptychography, a sample is rastered through a focused x-ray beam with varying photon energy so that a series of phaseless diffraction data are recorded. Each chemical component in the material under investigation has a characteristic absorption and phase contrast as a function of photon energy. Using a dictionary formed by the set of contrast functions of each energy for each chemical component, it is possible to obtain the chemical composition of the material from high resolution multi-spectral images. This paper presents SPA (Spectroscopic Ptychography with ADMM), a novel algorithm to iteratively solve the spectroscopic blind ptychography problem. We design first a nonlinear spectro-ptychography model based on Poisson maximum likelihood, and construct then the proposed method based on fast iterative splitting operators. SPA can be used to retrieve spectral contrast when considering both a known or an incomplete (partially known) dictionary of reference spectra. By coupling the redundancy across different spectral measurements, the proposed algorithm can achieve higher reconstruction quality when compared to standard state-of-the-art two-step methods. We demonstrate how SPA can recover accurate chemical maps from Poisson-noised measurements, and also show its enhanced robustness when reconstructing reduced redundancy ptychography data using large scanning stepsizes.
    Keywords Electrical Engineering and Systems Science - Image and Video Processing ; Mathematics - Optimization and Control
    Subject code 006
    Publishing date 2019-05-31
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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  9. Book ; Online: Sparse Matrix-Based HPC Tomography

    Marchesini, Stefano / Trivedi, Anuradha / Enfedaque, Pablo / Perciano, Talita / Parkinson, Dilworth

    2020  

    Abstract: Tomographic imaging has benefited from advances in X-ray sources, detectors and optics to enable novel observations in science, engineering and medicine. These advances have come with a dramatic increase of input data in the form of faster frame rates, ... ...

    Abstract Tomographic imaging has benefited from advances in X-ray sources, detectors and optics to enable novel observations in science, engineering and medicine. These advances have come with a dramatic increase of input data in the form of faster frame rates, larger fields of view or higher resolution, so high performance solutions are currently widely used for analysis. Tomographic instruments can vary significantly from one to another, including the hardware employed for reconstruction: from single CPU workstations to large scale hybrid CPU/GPU supercomputers. Flexibility on the software interfaces and reconstruction engines are also highly valued to allow for easy development and prototyping. This paper presents a novel software framework for tomographic analysis that tackles all aforementioned requirements. The proposed solution capitalizes on the increased performance of sparse matrix-vector multiplication and exploits multi-CPU and GPU reconstruction over MPI. The solution is implemented in Python and relies on CuPy for fast GPU operators and CUDA kernel integration, and on SciPy for CPU sparse matrix computation. As opposed to previous tomography solutions that are tailor-made for specific use cases or hardware, the proposed software is designed to provide flexible, portable and high-performance operators that can be used for continuous integration at different production environments, but also for prototyping new experimental settings or for algorithmic development. The experimental results demonstrate how our implementation can even outperform state-of-the-art software packages used at advanced X-ray sources worldwide.
    Keywords Computer Science - Distributed ; Parallel ; and Cluster Computing
    Subject code 004
    Publishing date 2020-03-27
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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  10. Article ; Online: Sparse Matrix-Based HPC Tomography

    Marchesini, Stefano / Trivedi, Anuradha / Enfedaque, Pablo / Perciano, Talita / Parkinson, Dilworth

    Computational Science - ICCS 2020

    Abstract: Tomographic imaging has benefited from advances in X-ray sources, detectors and optics to enable novel observations in science, engineering and medicine. These advances have come with a dramatic increase of input data in the form of faster frame rates, ... ...

    Abstract Tomographic imaging has benefited from advances in X-ray sources, detectors and optics to enable novel observations in science, engineering and medicine. These advances have come with a dramatic increase of input data in the form of faster frame rates, larger fields of view or higher resolution, so high performance solutions are currently widely used for analysis. Tomographic instruments can vary significantly from one to another, including the hardware employed for reconstruction: from single CPU workstations to large scale hybrid CPU/GPU supercomputers. Flexibility on the software interfaces and reconstruction engines are also highly valued to allow for easy development and prototyping. This paper presents a novel software framework for tomographic analysis that tackles all aforementioned requirements. The proposed solution capitalizes on the increased performance of sparse matrix-vector multiplication and exploits multi-CPU and GPU reconstruction over MPI. The solution is implemented in Python and relies on CuPy for fast GPU operators and CUDA kernel integration, and on SciPy for CPU sparse matrix computation. As opposed to previous tomography solutions that are tailor-made for specific use cases or hardware, the proposed software is designed to provide flexible, portable and high-performance operators that can be used for continuous integration at different production environments, but also for prototyping new experimental settings or for algorithmic development. The experimental results demonstrate how our implementation can even outperform state-of-the-art software packages used at advanced X-ray sources worldwide.
    Keywords covid19
    Publisher PMC
    Document type Article ; Online
    DOI 10.1007/978-3-030-50371-0_18
    Database COVID19

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