Difference between revisions of "Projects/SRF: Syncrotron radiation facility deep image retrieval"
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				|  (Created page with "===Project 58 === * Title: X-ray nanotomographyimage reconstruction * Peoblem: To boost quality of nano-, полученных в лабораториях Европейско...") | |||
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| − | ===Project 58  | + | {{#seo: | 
| + |  |title=Syncrotron radiation facility deep image retrieval | ||
| + |  |titlemode=replace | ||
| + |  |keywords=Syncrotron radiation facility deep image retrieval | ||
| + |  |description=Projects/SRF: Syncrotron radiation facility deep image retrieval | ||
| + |  }} | ||
| + | ==Project 58 == | ||
| * Title: X-ray nanotomographyimage reconstruction | * Title: X-ray nanotomographyimage reconstruction | ||
| − | *  | + | * Problem: To boost the quality of nano-object images, obtained in the European Syncrotron Radiation Facility, [https://www.osug.fr/IMG/pdf/zontone_osug_workshop2017id10.pdf ESRF]. | 
| − | + | * Data: on your request, 3GB | |
| * References: | * References: | ||
| ** [https://arxiv.org/pdf/1809.04626.pdf] Iterative phase retrieval in coherent diffractive imaging: practical issues | ** [https://arxiv.org/pdf/1809.04626.pdf] Iterative phase retrieval in coherent diffractive imaging: practical issues | ||
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| ** [https://arxiv.org/pdf/1904.11301.pdf] DEEP ITERATIVE RECONSTRUCTION FOR PHASE RETRIEVAL | ** [https://arxiv.org/pdf/1904.11301.pdf] DEEP ITERATIVE RECONSTRUCTION FOR PHASE RETRIEVAL | ||
| ** [https://docs.google.com/document/d/1K7bIzU33MSfeUvg3WITRZX0pe3sibbtH62aw42wxsEI/edit?ts=5e42f70e LinkReview] | ** [https://docs.google.com/document/d/1K7bIzU33MSfeUvg3WITRZX0pe3sibbtH62aw42wxsEI/edit?ts=5e42f70e LinkReview] | ||
| − | ** AUSPEX is a diagnostic tool for graphical X- | + | ** AUSPEX is a diagnostic tool for graphical X-ray data analysis, see [https://www.auspex.de/pathol/ common pathologies and their causes] | 
| * Basic:  Gerchberg-Saxton algorithm   | * Basic:  Gerchberg-Saxton algorithm   | ||
| − | * Method: To boost Gerchberg-Saxton with neural networks. Use Bayesian approach and set physical models as expert-given prior information | + | * Method: To boost Gerchberg-Saxton with neural networks. Use the Bayesian approach and set physical models as expert-given prior information | 
| * Novelty: we are developing expert learning method | * Novelty: we are developing expert learning method | ||
| * Authors: Sergei Grudinin, Yuri Chushkin, and Vadim Strijov | * Authors: Sergei Grudinin, Yuri Chushkin, and Vadim Strijov | ||
Latest revision as of 00:28, 17 February 2024
Project 58
- Title: X-ray nanotomographyimage reconstruction
- Problem: To boost the quality of nano-object images, obtained in the European Syncrotron Radiation Facility, ESRF.
- Data: on your request, 3GB
- References:
- [1] Iterative phase retrieval in coherent diffractive imaging: practical issues
- [2] X-ray nanotomography of coccolithophores reveals that coccolith mass and segment number correlate with grid size
- [3] Lens-free microscopy for 3D + time acquisitions of 3D cell culture
- [4] DEEP ITERATIVE RECONSTRUCTION FOR PHASE RETRIEVAL
- LinkReview
- AUSPEX is a diagnostic tool for graphical X-ray data analysis, see common pathologies and their causes
 
- Basic: Gerchberg-Saxton algorithm
- Method: To boost Gerchberg-Saxton with neural networks. Use the Bayesian approach and set physical models as expert-given prior information
- Novelty: we are developing expert learning method
- Authors: Sergei Grudinin, Yuri Chushkin, and Vadim Strijov