ArticlePhilosophical transactions. Series A, Mathematical, physical, and engineering sciences2021
Core Imaging Library - Part II: multichannel reconstruction for dynamic and spectral tomography.
Article in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Dynamic laboratory x-ray phase-contrast microtomography with structure-based prior regularisation.Measurement science & technology · 2025Article
- Stochastic Primal-Dual Hybrid Gradient Algorithm with Adaptive Step Sizes.Journal of mathematical imaging and vision · 2024Article
- Quantifying multiple stain distributions in bioimaging by hyperspectral X-ray tomography.Scientific reports · 2022Article
- Enhanced hyperspectral tomography for bioimaging by spatiospectral reconstruction.Scientific reports · 2021Article
- Synergistic tomographic image reconstruction: part 2.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2021Article
- Core Imaging Library - Part I: a versatile Python framework for tomographic imaging.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2021Article
Corrections and comments
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Authors and funding
10 authors.
Funding
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Abstract
The newly developed core imaging library (CIL) is a flexible plug and play library for tomographic imaging with a specific focus on iterative reconstruction. CIL provides building blocks for tailored regularized reconstruction algorithms and explicitly supports multichannel tomographic data. In the first part of this two-part publication, we introduced the fundamentals of CIL. This paper focuses on applications of CIL for multichannel data, e.g. dynamic and spectral. We formalize different optimization problems for colour processing, dynamic and hyperspectral tomography and demonstrate CIL's capabilities for designing state-of-the-art reconstruction methods through case studies and code snapshots. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.