Robustness of data-driven approaches in limited angle tomography
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866908480459243520 |
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| author | Wang, Yiran Zhong, Yimin |
| author_facet | Wang, Yiran Zhong, Yimin |
| contents | The limited angle Radon transform is notoriously difficult to invert due to its ill-posedness. In this work, we give a mathematical explanation that data-driven approaches can stably reconstruct more information compared to traditional methods like filtered backprojection. In addition, we use experiments based on the U-Net neural network to validate our theory. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_11350 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Robustness of data-driven approaches in limited angle tomography Wang, Yiran Zhong, Yimin Numerical Analysis Machine Learning 35R30 The limited angle Radon transform is notoriously difficult to invert due to its ill-posedness. In this work, we give a mathematical explanation that data-driven approaches can stably reconstruct more information compared to traditional methods like filtered backprojection. In addition, we use experiments based on the U-Net neural network to validate our theory. |
| title | Robustness of data-driven approaches in limited angle tomography |
| topic | Numerical Analysis Machine Learning 35R30 |
| url | https://arxiv.org/abs/2403.11350 |