Minimizing the Number of Views in Few-View Computed Tomography: a Deep Learning Approach-Reference-Cited by-同舟云学术

Minimizing the Number of Views in Few-View Computed Tomography: a Deep Learning Approach

Published:2022-05-16 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)
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Author:

Vlasov V. V.¹,Konovalov A. B.¹

Affiliation:

1. Computational Center Federal State Unitary Enterprise “Russian Federal Nuclear Center – Zababakhin All-Russia Research Institute of Technical Physics”,Snezhinsk,Russia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9786772/9787073/09787247.pdf?arnumber=9787247

Reference23 articles.

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2. Few-Views Image Reconstruction with SMART and an Allowance for Contrast Structure Shadows

3. Hybrid algorithm for few-views computed tomography of strongly absorbing media: algebraic reconstruction, TV-regularization, and adaptive segmentation

4. Joint image reconstruction and segmentation: Comparison of two algorithms for few-view tomography

5. U-Net: Convolutional networks for biomedical image segmentation;ronneberger;Proc of MICCAI 2015 Part III N Navab et al Eds Lect Notes Comput Sci,0

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