001     1005339
005     20240131202657.0
024 7 _ |a 10.1093/micmic/ozad021
|2 doi
024 7 _ |a 1079-8501
|2 ISSN
024 7 _ |a 1431-9276
|2 ISSN
024 7 _ |a 1435-8115
|2 ISSN
024 7 _ |a 2128/34546
|2 Handle
024 7 _ |a WOS:001005190700012
|2 WOS
037 _ _ |a FZJ-2023-01445
041 _ _ |a English
082 _ _ |a 500
100 1 _ |a Bangun, Arya
|0 P:(DE-Juel1)184644
|b 0
|e Corresponding author
|u fzj
245 _ _ |a Wigner Distribution Deconvolution Adaptation for Live Ptychography Reconstruction
260 _ _ |a New York, NY
|c 2023
|b Cambridge University Press
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1706693074_5584
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a We propose a modification of Wigner distribution deconvolution (WDD) to support live processing ptychography. Live processing allows to reconstruct and display the specimen transmission function gradually while diffraction patterns are acquired. For this purpose, we reformulate WDD and apply a dimensionality reduction technique that reduces memory consumption and increases processing speed. We show numerically that this approach maintains the reconstruction quality of specimen transfer functions as well as reduces computational complexity during acquisition processes. Although we only present the reconstruction for scanning transmission electron microscopy datasets, in general, the live processing algorithm we present in this paper can be applied to real-time ptychographic reconstruction for different fields of application.
536 _ _ |a 5351 - Platform for Correlative, In Situ and Operando Characterization (POF4-535)
|0 G:(DE-HGF)POF4-5351
|c POF4-535
|f POF IV
|x 0
536 _ _ |a 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511)
|0 G:(DE-HGF)POF4-5111
|c POF4-511
|f POF IV
|x 1
588 _ _ |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de
700 1 _ |a Baumeister, Paul F
|0 P:(DE-Juel1)156619
|b 1
700 1 _ |a Clausen, Alexander
|0 P:(DE-Juel1)174151
|b 2
700 1 _ |a Weber, Dieter
|0 P:(DE-Juel1)171370
|b 3
700 1 _ |a Dunin-Borkowski, Rafal E
|0 P:(DE-Juel1)144121
|b 4
773 _ _ |a 10.1093/micmic/ozad021
|g p. ozad021
|0 PERI:(DE-600)1481716-0
|n 3
|p 994–1008
|t Microscopy and microanalysis
|v 29
|y 2023
|x 1079-8501
856 4 _ |u https://juser.fz-juelich.de/record/1005339/files/Invoice_E16024168.pdf
856 4 _ |u https://juser.fz-juelich.de/record/1005339/files/ozad021.pdf
|y OpenAccess
909 C O |o oai:juser.fz-juelich.de:1005339
|p openaire
|p open_access
|p OpenAPC
|p driver
|p VDB
|p openCost
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)184644
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)156619
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)174151
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 3
|6 P:(DE-Juel1)171370
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 4
|6 P:(DE-Juel1)144121
913 1 _ |a DE-HGF
|b Key Technologies
|l Materials Systems Engineering
|1 G:(DE-HGF)POF4-530
|0 G:(DE-HGF)POF4-535
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Materials Information Discovery
|9 G:(DE-HGF)POF4-5351
|x 0
913 1 _ |a DE-HGF
|b Key Technologies
|l Engineering Digital Futures – Supercomputing, Data Management and Information Security for Knowledge and Action
|1 G:(DE-HGF)POF4-510
|0 G:(DE-HGF)POF4-511
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Enabling Computational- & Data-Intensive Science and Engineering
|9 G:(DE-HGF)POF4-5111
|x 1
914 1 _ |y 2023
915 p c |a APC keys set
|0 PC:(DE-HGF)0000
|2 APC
915 p c |a Local Funding
|0 PC:(DE-HGF)0001
|2 APC
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2022-11-08
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1190
|2 StatID
|b Biological Abstracts
|d 2022-11-08
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2022-11-08
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
|d 2023-08-22
|w ger
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b MICROSC MICROANAL : 2022
|d 2023-08-22
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2023-08-22
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2023-08-22
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2023-08-22
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
|d 2023-08-22
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2023-08-22
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
|d 2023-08-22
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1150
|2 StatID
|b Current Contents - Physical, Chemical and Earth Sciences
|d 2023-08-22
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2023-08-22
920 _ _ |l yes
920 1 _ |0 I:(DE-Juel1)ER-C-1-20170209
|k ER-C-1
|l Physik Nanoskaliger Systeme
|x 0
920 1 _ |0 I:(DE-Juel1)JSC-20090406
|k JSC
|l Jülich Supercomputing Center
|x 1
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-Juel1)ER-C-1-20170209
980 _ _ |a I:(DE-Juel1)JSC-20090406
980 _ _ |a APC
980 _ _ |a UNRESTRICTED
980 1 _ |a APC
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21