Unsupervised classification for region of interest in X-ray ptychography
Abstract X-ray ptychography offers high-resolution imaging of large areas at a high computational cost due to the large volume of data provided. To address the cost issue, we propose a physics-informed unsupervised classification algorithm that is performed prior to reconstruction and removes data o...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-11-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-45336-4 |
| _version_ | 1797576756371128320 |
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| author | Dergan Lin Yi Jiang Junjing Deng Zichao Wendy Di |
| author_facet | Dergan Lin Yi Jiang Junjing Deng Zichao Wendy Di |
| author_sort | Dergan Lin |
| collection | DOAJ |
| description | Abstract X-ray ptychography offers high-resolution imaging of large areas at a high computational cost due to the large volume of data provided. To address the cost issue, we propose a physics-informed unsupervised classification algorithm that is performed prior to reconstruction and removes data outside the region of interest (RoI) based on the multimodal features present in the diffraction patterns. The preprocessing time for the proposed method is inconsequential in contrast to the resource-intensive reconstruction process, leading to an impressive reduction in the data workload to a mere 20% of the initial dataset. This capability consequently reduces computational time dramatically while preserving reconstruction quality. Through further segmentation of the diffraction patterns, our proposed approach can also detect features that are smaller than beam size and correctly classify them as within the RoI. |
| first_indexed | 2024-03-10T21:59:11Z |
| format | Article |
| id | doaj.art-35d22d7b3f2b46b8a3def38d6a9d2d16 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-10T21:59:11Z |
| publishDate | 2023-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-35d22d7b3f2b46b8a3def38d6a9d2d162023-11-19T13:01:18ZengNature PortfolioScientific Reports2045-23222023-11-0113111210.1038/s41598-023-45336-4Unsupervised classification for region of interest in X-ray ptychographyDergan Lin0Yi Jiang1Junjing Deng2Zichao Wendy Di3Mathematics and Computer Science Division, Argonne National LaboratoryAdvanced Photon Source, Argonne National LaboratoryAdvanced Photon Source, Argonne National LaboratoryMathematics and Computer Science Division, Argonne National LaboratoryAbstract X-ray ptychography offers high-resolution imaging of large areas at a high computational cost due to the large volume of data provided. To address the cost issue, we propose a physics-informed unsupervised classification algorithm that is performed prior to reconstruction and removes data outside the region of interest (RoI) based on the multimodal features present in the diffraction patterns. The preprocessing time for the proposed method is inconsequential in contrast to the resource-intensive reconstruction process, leading to an impressive reduction in the data workload to a mere 20% of the initial dataset. This capability consequently reduces computational time dramatically while preserving reconstruction quality. Through further segmentation of the diffraction patterns, our proposed approach can also detect features that are smaller than beam size and correctly classify them as within the RoI.https://doi.org/10.1038/s41598-023-45336-4 |
| spellingShingle | Dergan Lin Yi Jiang Junjing Deng Zichao Wendy Di Unsupervised classification for region of interest in X-ray ptychography Scientific Reports |
| title | Unsupervised classification for region of interest in X-ray ptychography |
| title_full | Unsupervised classification for region of interest in X-ray ptychography |
| title_fullStr | Unsupervised classification for region of interest in X-ray ptychography |
| title_full_unstemmed | Unsupervised classification for region of interest in X-ray ptychography |
| title_short | Unsupervised classification for region of interest in X-ray ptychography |
| title_sort | unsupervised classification for region of interest in x ray ptychography |
| url | https://doi.org/10.1038/s41598-023-45336-4 |
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