Difference between revisions of "Projects/SRF: Syncrotron radiation facility deep image retrieval"

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===Project 58 ===
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==Project 58 ==
 
* Title: X-ray nanotomographyimage reconstruction
 
* Title: X-ray nanotomographyimage reconstruction
* Peoblem: To boost quality of nano-object images, obtained in the European Syncrotron Radiation Facility, [https://www.osug.fr/IMG/pdf/zontone_osug_workshop2017id10.pdf ESRF].
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* 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
 
* Data: on your request, 3GB
 
* References:
 
* References:
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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-Ray data analysis, see [https://www.auspex.de/pathol/ common pathologies and their causes]
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** 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
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* 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