Fast digital lossy compression for X-ray ptychographic data

Huang, Panpan; Du, Ming; Hammer, Mike; Miceli, Antonino; Jacobsen, Chris

doi:10.1107/s1600577520013326

Cited by 10 publications

(11 citation statements)

References 39 publications

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“…This analysis has made clear several challenges that should be resolved to fully exploit the worldwide investment in diffraction-limited storage ring light sources. If we use ptychography as a particularly dose-efficient and non-opticslimited imaging approach, we will need dramatic advances in the available frame rate of detectors with a modest number of pixels, such as megahertz frame rates for 256 2 pixels (ondetector lossy data compression might help in reaching this performance level; Huang et al, 2021). We will need improved high-speed scanning systems and 'smart' scanning systems to potentially adjust the cumulative number of photons used per voxel to collect a larger signal where needed for critical feature identification and a smaller signal from other regions.…”

Section: Resultsmentioning

confidence: 99%

Upscaling X-ray nanoimaging to macroscopic specimens

Du¹,

Zw²,

Gürsoy³

et al. 2021

J Appl Crystallogr

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Upscaling X-ray nanoimaging to macroscopic specimens has the potential for providing insights across multiple length scales, but its feasibility has long been an open question. By combining the imaging requirements and existing proof-of-principle examples in large-specimen preparation, data acquisition and reconstruction algorithms, the authors provide imaging time estimates for howX-ray nanoimaging can be scaled to macroscopic specimens. To arrive at this estimate, a phase contrast imaging model that includes plural scattering effects is used to calculate the required exposure and corresponding radiation dose. The coherent X-ray flux anticipated from upcoming diffraction-limited light sources is then considered. This imaging time estimation is in particular applied to the case of the connectomes of whole mouse brains. To image the connectome of the whole mouse brain, electron microscopy connectomics might require years, whereas optimized X-ray microscopy connectomics could reduce this to one week. Furthermore, this analysis points to challenges that need to be overcome (such as increased X-ray detector frame rate) and opportunities that advances in artificial-intelligence-based `smart' scanning might provide. While the technical advances required are daunting, it is shown that X-ray microscopy is indeed potentially applicable to nanoimaging of millimetre- or even centimetre-size specimens.

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Section: Resultsmentioning

confidence: 99%

Upscaling X-ray nanoimaging to macroscopic specimens

Du¹,

Zw²,

Gürsoy³

et al. 2021

J Appl Crystallogr

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“…To reduce data size, this package utilized a lossy compression method that encoded the number of photons captured on single pixel into 8-bit integers. Huang et al 35 extended this compression method into their compression schemes. They encoded the number of photons on single pixel using a quasi-linear transform by introducing a bit-shift divisor and an offset value.…”

Section: Review Of Compression Techniquesmentioning

confidence: 99%

“…Huang et al 35 's work extended the work of 34 and successfully proposed three schemes for data compression by manipulating the parameters of the transform. The impact of data compression to the original data was thoroughly examined with evaluations of reconstruction error and spatial resolution.…”

Section: Review Of Compression Techniquesmentioning

confidence: 99%

Software and algorithms for high-throughput multimodal experiments at advanced synchrotron light sources

Li¹,

Zhang²,

Liu³

et al. 2023

Conference on Infrared, Millimeter, Terahertz Waves and Applications (IMT2022)

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With advancements on synchrotron radiation instrumentations particularly the emergence of next-generation light sources with ultra-low emittance and high intensity, scientific experiments have shifted from 2D static to multidimensional dynamic characterizations with multimodal approaches, enabling new capabilities of probing structural and functional changes across multiple length scales with extreme spatial and temporal resolution. However, such advancement on synchrotron hardware imposes tremendous challenges on the data processing end. Effective software tools and algorithms addressing image denoising, segmentation and data compression problems can be of great use to alleviate the burden, fully releasing the power of advanced instrumentations. Instead of separately utilizing modular image processing algorithms, this review suggests a unified experimental control and data acquisition software framework that naturally interfaces and integrates advanced software and algorithms with extensive AI assistance would be best suitable for next-generation beamlines. The review will also discuss prospective applications artificial intelligence and large-scale high performance computing infrastructures could bring about to facilitate scientific discoveries at next-generation synchrotron light sources.

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“…By performing some simple digital operations on the ADC output, the number of bits per sample can be reduced with little loss of information. In a companion paper, we have shown that using only 8 or 9 bits has a negligible effect on the ptychographic image reconstructions [15]. This section describes an in-pixel encoding scheme where the ADC value is digitally divided to create an encoded sequence with reduced bit count.…”

Section: Digitally Encoding the Adc Output Near The Photon Poisson Noisementioning

confidence: 99%

Strategies for on-chip digital data compression for X-ray pixel detectors

Hammer,

Yoshii,

Miceli

2020

Preprint

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As frame rates of X-ray pixel detectors continue to increase, photon counting will be replaced with charge-integrating pixel array detectors for high dynamic range applications. The continued desire for faster frame rates will also stress the ability of application-specific integrated circuit (ASIC) designers to provide sufficient off-chip bandwidth to reach continuous frame rates of 1 MHz. To move from the current 10 kHz to the 1 MHz frame rate regime, ASIC designers will continue to pack as many power-hungry high-speed transceivers at the periphery of the ASIC as possible. In this paper, however, we present new strategies to make the most efficient use of the off-chip bandwidth by utilizing data compression schemes for X-ray photon-counting and chargeintegrating pixel detectors. In particular, we describe a novel in-pixel compression scheme that converts from analog to digital converter units to encoded photon counts near the photon Poisson noise level which achieves a compression ratio of > 1.5× independent of the dataset. In addition, we describe a simple yet efficient zero-suppression compression scheme called "zeromask" (ZM) located at the ASIC's edge before streaming data off the ASIC chip. ZM achieves an average compression ratios of > 4×, > 7×, and > 8× for high-energy X-ray diffraction, ptychography, and X-ray photon correlation spectroscopy datasets, respectively. We present the conceptual designs, register-transfer level (RTL) block diagrams, and the physical ASIC implementation of these compression schemes in 65 nm CMOS. When combined, these two digital compression schemes can increase off-chip bandwidth by a factor of 6-12×.

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Fast digital lossy compression for X-ray ptychographic data

Cited by 10 publications

References 39 publications

Upscaling X-ray nanoimaging to macroscopic specimens

Upscaling X-ray nanoimaging to macroscopic specimens

Software and algorithms for high-throughput multimodal experiments at advanced synchrotron light sources

Strategies for on-chip digital data compression for X-ray pixel detectors

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