The DOI matches its Crossref record; 42 of the 42 references it cites were found in a registry or an index.
High-performance iterative electron tomography reconstruction with long-object compensation using graphics processing units (GPUs)
Open accessAbstract
Iterative reconstruction algorithms pose tremendous computational challenges for 3D Electron Tomography (ET). Similar to X-ray Computed Tomography (CT), graphics processing units (GPUs) offer an affordable platform to meet these demands. In this paper, we outline a CT reconstruction approach for ET that is optimized for the special demands and application setting of ET. It exploits the fact that ET is typically cast as a parallel-beam configuration, which allows the design of an efficient data management scheme, using a holistic sinogram-based representation. Our method produces speedups of about an order of magnitude over a previously proposed GPU-based ET implementation, on similar hardware, and completes an iterative 3D reconstruction of practical problem size within minutes. We also describe a novel GPU-amenable approach that effectively compensates for reconstruction errors resulting from the TEM data acquisition on (long) samples which extend the width of the parallel TEM beam. We show that the vignetting artifacts typically arising at the periphery of non-compensated ET reconstructions are completely eliminated when our method is employed.
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Herraiz ve diğerleri [25] pozitron emisyon tomografisi görüntülerini ileri ve geri projeksiyon yöntemi ile geriçatmış ve GPU ile CPU'ya göre 72 kata kadar hızlandırmışlardır.
“Herraiz ve diğerleri [25] ise çalışmalarında pozitron emisyon tomografisi ile elde edilen görüntüleri ileri ve geri projeksiyon yöntemini kullanarak geriçatmaktadırlar. Bu işlemi GPU ile CPU'ya göre 72 kata kadar hızlandırmışlardır.”
From GPU Programlamada CUDA Platformu Kullanılan Paralel Görüntü İşleme Çalışmalarının İncelenmesi (2020) · cites this paper as [25]
The Results section identifies the reconstructed data as electron-microscopy images of a virus and a brain synapse, not positron-emission tomography images. The Methods section does describe GPU-accelerated forward and back projection, but the cited paper is by Xu and colleagues, not Herraiz and colleagues, and its performance discussion does not report the claimed 72-fold GPU-versus-CPU speedup. (LLM, conf=0.88)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredİncelenen görüntü geriçatma çalışmalarında ileri ve geri izdüşüm yöntemi CUDA ile paralelleştirmede en çok kullanılan yöntemdir.
“İncelenen çalışmalarda görüntü geriçatmada ileri ve geri izdüşüm yönteminin CUDA ile paralelleştirmede en çok kullanılan yöntem olduğu görülmektedir [22, 23, 24, 25].”
From GPU Programlamada CUDA Platformu Kullanılan Paralel Görüntü İşleme Çalışmalarının İncelenmesi (2020) · cites this paper as [25]
Section 3.1 describes parallelizing forward and back projection for image reconstruction. But the Introduction states that this paper’s implementation uses GLSL, not CUDA, and the paper does not establish that this is the most commonly used CUDA approach among the studies reviewed by the citing authors. Our copy provides no page numbers for these passages. (LLM, conf=0.87)
Experimental — accuracy not yet measured
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Research works printed but not linked: 1
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“Palenstijn ve diğerleri [28] 2011 yılında yaptıkları çalışmada Xu ve diğerlerinin [26] çalışmasını iyileştirmişlerdir.”
Metadata
- Authors
- Xu, W., Xu, F., Jones, M., Keszthelyi, B., Sedat, J., Agard, D., & Mueller, K.
- Affiliations
- Stony Brook University (US)
- Howard Hughes Medical Institute (US)
- University of California, San Francisco (US)
- Corresponding author
- Mueller, Klaus
- Venue
- Journal of Structural Biology
- Publisher
- Elsevier BV
- Published
- 2010-08
- Volume
- 171
- Issue
- 2
- Pages
- 142-153
- ISSN
- 1047-8477 (ISSN-L)
- PMC
- PMC2885506
- OpenAlex
- W2126753599
- Cited by
- 71
- References
- 42
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 1 · 2022: 2 · 2021: 3 · 2020: 4 · 2019: 5 · 2018: 3 · 2017: 5 · 2016: 4 · 2015: 7 · 2014: 6 · 2013: 10 · 2012: 8
- FWCI
- 5.09
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- Journal of Structural Biology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Science Foundation
- Howard Hughes Medical Institute
- W. M. Keck Foundation
- National Institutes of Health (5r21eb004099-02)
- National Institute of General Medical Sciences (GM 31627, R01GM031627)
- National Institute of Biomedical Imaging and Bioengineering (R21 EB004099, R21 EB004099-01)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Advanced Electron Microscopy Techniques and Applications
- Physical Sciences › Computer Science › Hardware and Architecture › Parallel Computing and Optimization Techniques
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Computer Graphics and Visualization Techniques
- Keywords
- electron tomography, iterative reconstruction, GPU acceleration, parallel-beam tomography, 3D reconstruction
- MeSH terms
- Algorithms, Image Processing, Computer-Assisted, Electron Microscope Tomography
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