Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2401.02454 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866916284477734912 |
|---|---|
| author | Wu, Longlong Yoo, Shinjae Chu, Yong S. Huang, Xiaojing Robinson, Ian K. |
| author_facet | Wu, Longlong Yoo, Shinjae Chu, Yong S. Huang, Xiaojing Robinson, Ian K. |
| contents | Ptychography, as a powerful lensless imaging method, has become a popular member of the coherent diffractive imaging family over decades of development. The ability to utilize low-dose X-rays and/or fast scans offers a big advantage in a ptychographic measurement (for example, when measuring radiation-sensitive samples), but results in low-photon statistics, making the subsequent phase retrieval challenging. Here, we demonstrate a dose-efficient automatic differentiation framework for ptychographic reconstruction (DAP) at low-photon statistics and low overlap ratio. As no reciprocal space constraint is required in this DAP framework, the framework, based on various forward models, shows superior performance under these conditions. It effectively suppresses potential artifacts in the reconstructed images, especially for the inherent periodic artifact in a raster scan. We validate the effectiveness and robustness of this method using both simulated and measured datasets. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_02454 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Dose-efficient Automatic Differentiation for Ptychographic Reconstruction Wu, Longlong Yoo, Shinjae Chu, Yong S. Huang, Xiaojing Robinson, Ian K. Medical Physics Optics Ptychography, as a powerful lensless imaging method, has become a popular member of the coherent diffractive imaging family over decades of development. The ability to utilize low-dose X-rays and/or fast scans offers a big advantage in a ptychographic measurement (for example, when measuring radiation-sensitive samples), but results in low-photon statistics, making the subsequent phase retrieval challenging. Here, we demonstrate a dose-efficient automatic differentiation framework for ptychographic reconstruction (DAP) at low-photon statistics and low overlap ratio. As no reciprocal space constraint is required in this DAP framework, the framework, based on various forward models, shows superior performance under these conditions. It effectively suppresses potential artifacts in the reconstructed images, especially for the inherent periodic artifact in a raster scan. We validate the effectiveness and robustness of this method using both simulated and measured datasets. |
| title | Dose-efficient Automatic Differentiation for Ptychographic Reconstruction |
| topic | Medical Physics Optics |
| url | https://arxiv.org/abs/2401.02454 |