يعرض 1 - 10 نتائج من 42 نتيجة بحث عن '"sparse-angle"', وقت الاستعلام: 0.99s تنقيح النتائج
  1. 1
    دورية أكاديمية
    Artifact Removal in Sparse-Angle CT Based on Feature Fusion Residual Network

    المؤلفون: Xie, S., Yang, T.

    المصدر: IEEE Transactions on Radiation and Plasma Medical Sciences IEEE Trans. Radiat. Plasma Med. Sci. Radiation and Plasma Medical Sciences, IEEE Transactions on. 5(2):261-271 Mar, 2021

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  2. 2
    دورية أكاديمية
    Undersampled Dynamic X-Ray Tomography With Dimension Reduction Kalman Filter

    المؤلفون: Hakkarainen, J., Purisha, Z., Solonen, A., Siltanen, S.

    المصدر: IEEE Transactions on Computational Imaging IEEE Trans. Comput. Imaging Computational Imaging, IEEE Transactions on. 5(3):492-501 Sep, 2019

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  3. 3
    مؤتمر
    Adaptive low-dose CT reconstruction

    المؤلفون: Zhao, Bingjie, Feng, Cuixia, Feng, Congcong, Wen, Junhai

    المصدر: 2015 8th International Congress on Image and Signal Processing (CISP) Image and Signal Processing (CISP), 2015 8th International Congress on. :712-716 Oct, 2015

    Relation: 2015 8th International Congress on Image and Signal Processing (CISP)

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  4. 4
    دورية أكاديمية
    Tomographic Imaging of Surface Deformation From Scarce Measurements via Sinogram Recovery

    المؤلفون: Constantino, E. P. A., Ozanyan, K. B.

    المصدر: IEEE Sensors Journal IEEE Sensors J. Sensors Journal, IEEE. 9(4):399-410 Apr, 2009

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  5. 5
    دورية أكاديمية
    A stacked dense denoising–segmentation network for undersampled tomograms and knowledge transfer using synthetic tomograms

    المؤلفون: Bellos, DimitriosAff1, Basham, MarkAff2, Aff3, Pridmore, Tony, French, Andrew P.

    المصدر: Machine Vision and Applications. 32(3)

    Find this article in full text from Springer Verlag. Find this article in full text from ProQuest Full Text Finder
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  6. 6
    دورية أكاديمية
    Quantitative Comparison of Deep Learning-Based Image Reconstruction Methods for Low-Dose and Sparse-Angle CT Applications

    المؤلفون: Johannes Leuschner, Maximilian Schmidt, Poulami Somanya Ganguly, Vladyslav Andriiashen, Sophia Bethany Coban, Alexander Denker, Dominik Bauer, Amir Hadjifaradji, Kees Joost Batenburg, Peter Maass, Maureen van Eijnatten

    المصدر: Journal of Imaging, Vol 7, Iss 3, p 44 (2021)

    مصطلحات موضوعية: computed tomography (CT), image reconstruction, low-dose, sparse-angle, deep learning, quantitative comparison, Photography, TR1-1050, Computer applications to medicine. Medical informatics, R858-859.7, Electronic computers. Computer science, QA75.5-76.95

    وصف الملف: electronic resource

    Relation: https://www.mdpi.com/2313-433X/7/3/44; https://doaj.org/toc/2313-433X

    URL الوصول: https://doaj.org/article/a9c9ce94377745e8adb2466faaf9be04

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  7. 7
    دورية أكاديمية
    Analytic Computed Tomography Reconstruction in Sparse-Angular Sampling Using a Sinogram-Normalization Interpolation Method

    المؤلفون: Kim, Guna, Park, Chulkyu, Lee, Dongyeon, Cho, HyosungAff1, Seo, Changwoo, Park, Soyoung, Kim, Kyuseok, Lim, Hyunwoo, Lee, Hunwoo, Kang, Seokyoon, Park, Jeongeun, Jeon, Duhee, Kim, Woosung, Lim, Younghwan

    المصدر: Journal of the Korean Physical Society. 73(3):361-367

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  8. 8
    دورية أكاديمية

    لا يتم عرض هذه النتيجة على الضيوف.

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  9. 9
    Quantitative Comparison of Deep Learning-Based Image Reconstruction Methods for Low-Dose and Sparse-Angle CT Applications

    المصدر: Journal of Imaging. 7(3)

    مصطلحات موضوعية: Quantitative comparison, Image reconstruction, Low-dose, Sparse-angle, Deep learning, Computed tomography (CT)

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=dris___00893::22870d31ee7cfddd4b9fecda4bcbfd34
    https://doi.org/10.3390/jimaging7030044

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  10. 10
    Quantitative Comparison of Deep Learning-Based Image Reconstruction Methods for Low-Dose and Sparse-Angle CT Applications

    المؤلفون: Leuschner, Johannes, Schmidt, Maximilian, Ganguly, Poulami Somanya, Andriiashen, Vladyslav, Coban, Sophia Bethany, Denker, Alexander, Bauer, Dominik, Hadjifaradji, Amir, Batenburg, Kees Joost, Maass, Peter, Van Eijnatten, Maureen

    المساهمون: Medical Image Analysis, EAISI Health

    المصدر: Journal of Imaging, Vol 7, Iss 44, p 44 (2021)
    Journal of Imaging
    Volume 7
    Issue 3
    Journal of Imaging, 7(3):44. Multidisciplinary Digital Publishing Institute (MDPI)
    Journal of Imaging, 7, 44.1-44.49

    مصطلحات موضوعية: low-dose, sparse-angle, quantitative comparison, deep learning, lcsh:R858-859.7, lcsh:Photography, lcsh:Electronic computers. Computer science, computed tomography (CT), image reconstruction, lcsh:TR1-1050, lcsh:Computer applications to medicine. Medical informatics, Article, lcsh:QA75.5-76.95

    وصف الملف: application/pdf

    URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::735ad229385ba6689a2b602315ea7093
    https://www.mdpi.com/2313-433X/7/3/44

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