000639323 001__ 639323
000639323 005__ 20251119161922.0
000639323 0247_ $$2doi$$a10.1364/OE.569216
000639323 0247_ $$2datacite_doi$$a10.3204/PUBDB-2025-04424
000639323 0247_ $$2altmetric$$aaltmetric:180505529
000639323 0247_ $$2pmid$$apmid:40984363
000639323 0247_ $$2openalex$$aopenalex:W4412831869
000639323 037__ $$aPUBDB-2025-04424
000639323 041__ $$aEnglish
000639323 082__ $$a530
000639323 1001_ $$0P:(DE-H253)PIP1082336$$aYang, Xiaogang$$b0$$eCorresponding author
000639323 245__ $$aSelf-supervised physics-informed generative networks for phase retrieval from a single X-ray hologram
000639323 260__ $$aWashington, DC$$bOptica$$c2025
000639323 3367_ $$2DRIVER$$aarticle
000639323 3367_ $$2DataCite$$aOutput Types/Journal article
000639323 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1762514190_3427885
000639323 3367_ $$2BibTeX$$aARTICLE
000639323 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000639323 3367_ $$00$$2EndNote$$aJournal Article
000639323 520__ $$aX-ray phase contrast imaging significantly improves the visualization of structures with weak or uniform absorption, broadening its applications across a wide range of scientific disciplines. Propagation-based phase contrast is particularly suitable for time- or dose-critical in vivo/in situ/operando (tomography) experiments because it requires only a single intensity measurement. However, the phase information of the wave field is lost during the measurement and must be recovered. Conventional algebraic and iterative methods often rely on specific approximations or boundary conditions that may not be met by many samples or experimental setups. In addition, they require manual tuning of reconstruction parameters by experts, making them less adaptable for complex or variable conditions. Here we present a self-learning approach for solving the inverse problem of phase retrieval in the near-field regime of Fresnel theory using a single intensity measurement (hologram). A physics-informed generative adversarial network is employed to reconstruct both the phase and absorbance of the unpropagated wave field in the sample plane from a single hologram. Unlike most state-of-the-art deep learning approaches for phase retrieval, our approach does not require paired, unpaired, or simulated training data. This significantly broadens the applicability of our approach, as acquiring or generating suitable training data remains a major challenge due to the wide variability in sample types and experimental configurations. The algorithm demonstrates robust and consistent performance across diverse imaging conditions and sample types, delivering quantitative, high-quality reconstructions for both simulated data and experimental datasets acquired at beamline P05 at PETRA III (DESY, Hamburg), operated by Helmholtz-Zentrum Hereon. Furthermore, it enables the simultaneous retrieval of both phase and absorption information. 
000639323 536__ $$0G:(DE-HGF)POF4-632$$a632 - Materials – Quantum, Complex and Functional Materials (POF4-632)$$cPOF4-632$$fPOF IV$$x0
000639323 536__ $$0G:(DE-HGF)POF4-6G3$$a6G3 - PETRA III (DESY) (POF4-6G3)$$cPOF4-6G3$$fPOF IV$$x1
000639323 536__ $$0G:(GEPRIS)221133217$$aSFB 986 Z02 - Multiskalige Analyse von Strukturen und Prozessen mit Synchrotronstrahlung und Neutronen (Z02) (221133217)$$c221133217$$x2
000639323 536__ $$0G:(DE-Ds200)BMBF-05D23CG1$$a05D23CG1 - Verbundprojekt 05D2022 - KI4D4E: Ein KI-basiertes Framework für die Visualisierung und Auswertung der massiven Datenmengen der 4D-Tomographie für Endanwender von Beamlines. Teilprojekt 7. (BMBF-05D23CG1)$$cBMBF-05D23CG1$$f05D23CG1$$x3
000639323 536__ $$0G:(DE-H253)I-20180109$$aFS-Proposal: I-20180109 (I-20180109)$$cI-20180109$$x4
000639323 536__ $$0G:(DE-H253)I-20191467$$aFS-Proposal: I-20191467 (I-20191467)$$cI-20191467$$x5
000639323 588__ $$aDataset connected to CrossRef, Journals: bib-pubdb1.desy.de
000639323 693__ $$0EXP:(DE-H253)P-P05-20150101$$1EXP:(DE-H253)PETRAIII-20150101$$6EXP:(DE-H253)P-P05-20150101$$aPETRA III$$fPETRA Beamline P05$$x0
000639323 7001_ $$0P:(DE-H253)PIP1100910$$aHailu, Dawit$$b1
000639323 7001_ $$0P:(DE-H253)PIP1099554$$aKulvait, Vojtěch$$b2
000639323 7001_ $$0P:(DE-H253)PIP1089222$$aJentschke, Thomas$$b3
000639323 7001_ $$0P:(DE-H253)PIP1030015$$aFlenner, Silja$$b4
000639323 7001_ $$0P:(DE-H253)PIP1009579$$aGreving, Imke$$b5
000639323 7001_ $$00000-0001-7079-0878$$aCampbell, Stuart I.$$b6
000639323 7001_ $$0P:(DE-H253)PIP1025514$$aHagemann, Johannes$$b7
000639323 7001_ $$0P:(DE-H253)PIP1008438$$aSchroer, Christian G.$$b8
000639323 7001_ $$0P:(DE-H253)PIP1106508$$aWong, Tak Ming$$b9
000639323 7001_ $$0P:(DE-H253)PIP1030371$$aMoosmann, Julian$$b10
000639323 773__ $$0PERI:(DE-600)1491859-6$$a10.1364/OE.569216$$gVol. 33, no. 17, p. 35832 -$$n17$$p35832 $$tOptics express$$v33$$x1094-4087$$y2025
000639323 8564_ $$uhttps://bib-pubdb1.desy.de/record/639323/files/Self-supervised%20physics-informed%20generative.pdf$$yOpenAccess
000639323 8564_ $$uhttps://bib-pubdb1.desy.de/record/639323/files/Self-supervised%20physics-informed%20generative.pdf?subformat=pdfa$$xpdfa$$yOpenAccess
000639323 909CO $$ooai:bib-pubdb1.desy.de:639323$$pdnbdelivery$$pdriver$$pVDB$$popen_access$$popenaire
000639323 9101_ $$0I:(DE-HGF)0$$6P:(DE-H253)PIP1082336$$aExternal Institute$$b0$$kExtern
000639323 9101_ $$0I:(DE-HGF)0$$6P:(DE-H253)PIP1100910$$aExternal Institute$$b1$$kExtern
000639323 9101_ $$0I:(DE-588b)1231250402$$6P:(DE-H253)PIP1100910$$aHelmholtz-Zentrum Hereon$$b1$$kHereon
000639323 9101_ $$0I:(DE-HGF)0$$6P:(DE-H253)PIP1099554$$aExternal Institute$$b2$$kExtern
000639323 9101_ $$0I:(DE-588b)1231250402$$6P:(DE-H253)PIP1099554$$aHelmholtz-Zentrum Hereon$$b2$$kHereon
000639323 9101_ $$0I:(DE-588b)16087541-9$$6P:(DE-H253)PIP1089222$$aHelmholtz-Zentrum Geesthacht$$b3$$kHZG
000639323 9101_ $$0I:(DE-HGF)0$$6P:(DE-H253)PIP1089222$$aExternal Institute$$b3$$kExtern
000639323 9101_ $$0I:(DE-588b)1231250402$$6P:(DE-H253)PIP1089222$$aHelmholtz-Zentrum Hereon$$b3$$kHereon
000639323 9101_ $$0I:(DE-588b)16087541-9$$6P:(DE-H253)PIP1030015$$aHelmholtz-Zentrum Geesthacht$$b4$$kHZG
000639323 9101_ $$0I:(DE-HGF)0$$6P:(DE-H253)PIP1030015$$aExternal Institute$$b4$$kExtern
000639323 9101_ $$0I:(DE-588b)1231250402$$6P:(DE-H253)PIP1030015$$aHelmholtz-Zentrum Hereon$$b4$$kHereon
000639323 9101_ $$0I:(DE-588b)16087541-9$$6P:(DE-H253)PIP1009579$$aHelmholtz-Zentrum Geesthacht$$b5$$kHZG
000639323 9101_ $$0I:(DE-588b)1231250402$$6P:(DE-H253)PIP1009579$$aHelmholtz-Zentrum Hereon$$b5$$kHereon
000639323 9101_ $$0I:(DE-588b)2008985-5$$6P:(DE-H253)PIP1025514$$aDeutsches Elektronen-Synchrotron$$b7$$kDESY
000639323 9101_ $$0I:(DE-588b)2008985-5$$6P:(DE-H253)PIP1008438$$aDeutsches Elektronen-Synchrotron$$b8$$kDESY
000639323 9101_ $$0I:(DE-588)1043621512$$6P:(DE-H253)PIP1008438$$aEuropean XFEL$$b8$$kXFEL.EU
000639323 9101_ $$0I:(DE-HGF)0$$6P:(DE-H253)PIP1106508$$aExternal Institute$$b9$$kExtern
000639323 9101_ $$0I:(DE-588b)1231250402$$6P:(DE-H253)PIP1106508$$aHelmholtz-Zentrum Hereon$$b9$$kHereon
000639323 9101_ $$0I:(DE-588b)16087541-9$$6P:(DE-H253)PIP1030371$$aHelmholtz-Zentrum Geesthacht$$b10$$kHZG
000639323 9101_ $$0I:(DE-588b)1231250402$$6P:(DE-H253)PIP1030371$$aHelmholtz-Zentrum Hereon$$b10$$kHereon
000639323 9131_ $$0G:(DE-HGF)POF4-632$$1G:(DE-HGF)POF4-630$$2G:(DE-HGF)POF4-600$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bForschungsbereich Materie$$lVon Materie zu Materialien und Leben$$vMaterials – Quantum, Complex and Functional Materials$$x0
000639323 9131_ $$0G:(DE-HGF)POF4-6G3$$1G:(DE-HGF)POF4-6G0$$2G:(DE-HGF)POF4-600$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bForschungsbereich Materie$$lGroßgeräte: Materie$$vPETRA III (DESY)$$x1
000639323 9141_ $$y2025
000639323 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2024-12-18
000639323 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2024-12-18
000639323 915__ $$0LIC:(DE-HGF)CCBY4$$2HGFVOC$$aCreative Commons Attribution CC BY 4.0
000639323 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bOPT EXPRESS : 2022$$d2024-12-18
000639323 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2024-05-08T07:03:57Z
000639323 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2024-05-08T07:03:57Z
000639323 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2024-12-18
000639323 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2024-12-18
000639323 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2024-12-18
000639323 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2024-12-18
000639323 915__ $$0StatID:(DE-HGF)0510$$2StatID$$aOpenAccess
000639323 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Anonymous peer review$$d2024-05-08T07:03:57Z
000639323 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$d2024-12-18
000639323 915__ $$0StatID:(DE-HGF)1150$$2StatID$$aDBCoverage$$bCurrent Contents - Physical, Chemical and Earth Sciences$$d2024-12-18
000639323 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2024-12-18
000639323 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2024-12-18
000639323 9201_ $$0I:(DE-H253)HAS-User-20120731$$kDOOR ; HAS-User$$lDOOR-User$$x0
000639323 9201_ $$0I:(DE-H253)Hereon-20210428$$kHereon$$lHelmholtz-Zentrum Hereon$$x1
000639323 9201_ $$0I:(DE-H253)FS-PETRA-20140814$$kFS-PETRA$$lFS-PETRA$$x2
000639323 980__ $$ajournal
000639323 980__ $$aVDB
000639323 980__ $$aUNRESTRICTED
000639323 980__ $$aI:(DE-H253)HAS-User-20120731
000639323 980__ $$aI:(DE-H253)Hereon-20210428
000639323 980__ $$aI:(DE-H253)FS-PETRA-20140814
000639323 9801_ $$aFullTexts