Studies on fast neutron imaging with a pixelated stilbene scintillator detector

Höflich, N.; Pooth, O.

doi:10.1016/j.nima.2022.167211

Nuclear Instruments and Methods in Physics Research Section A:

2022

DOI: 10.1016/j.nima.2022.167211

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Studies on fast neutron imaging with a pixelated stilbene scintillator detector

N. Höflich

O. Pooth

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2024

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“…The framework is open source under GPLv3 (GNU Public License v3.0), written in C++, and codeveloped by Vision Lab at the University of Antwerp and Centrum Wiskunde & Informatica (CWI) in Amsterdam. The ASTRA Toolbox has been used in multiple tomographic disciplines, e.g., ptychography [2] or neutron imaging [25], and serves as the back-end in several frameworks [23,42,26,3].…”

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confidence: 99%

ASTRA kernelkit: GPU-accelerated projectors for computed tomography using cupy

Graas,

Jan Palenstijn,

van Werkhoven

et al. 2024

AMMC

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New computed tomography (CT) algorithms are commonly developed in high-level programming languages, such as Python or MATLAB, while low-level languages are used to support their computation-intensive operations. In the past decade, graphics processing units (GPUs) have become the de-facto standard for large parallel computations in areas such as computational imaging, image processing, and machine learning. Our fast-and-flexible CT reconstruction software, ASTRA Toolbox, therefore already implemented tomographic projectors, i.e., the core computational operations modeling the X-ray physics, using NVIDIA CUDA (Compute Unified Device Architecture), a low-level platform for computation on GPUs. However, the Python-C++ language barrier prevents high-level Python users from modifying these lowlevel projectors, and, as a consequence, research into new tomographic algorithms is more complex and time-consuming than necessary. With the ASTRA KernelKit, we lifted tomographic projectors to Python and leveraged CuPy, a numerical software like NumPy and SciPy that exposes CUDA to Python, to obtain a fine-grained control over their efficiency and implementation. In this article, we introduced our software and illustrated its importance for highperformance and data-driven applications using examples from deep learning, real-time X-ray CT, and kernel tuning.

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mentioning

confidence: 99%

ASTRA kernelkit: GPU-accelerated projectors for computed tomography using cupy

Graas,

Jan Palenstijn,

van Werkhoven

et al. 2024

AMMC

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show abstract

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Studies on fast neutron imaging with a pixelated stilbene scintillator detector

Cited by 1 publication

References 7 publications

ASTRA kernelkit: GPU-accelerated projectors for computed tomography using cupy

ASTRA kernelkit: GPU-accelerated projectors for computed tomography using cupy

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