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dc.contributor.authorYeh, Li-Haoen_US
dc.contributor.authorTian, Leien_US
dc.contributor.authorWaller, Lauraen_US
dc.coverage.spatialUnited Statesen_US
dc.date.accessioned2017-05-09T13:35:10Z
dc.date.available2017-05-09T13:35:10Z
dc.date.issued2017-02-01
dc.identifierhttps://www.ncbi.nlm.nih.gov/pubmed/28270977
dc.identifier.citationLi-Hao Yeh, Lei Tian, Laura Waller. 2017. "Structured illumination microscopy with unknown patterns and a statistical prior.." Biomed Opt Express, Volume 8, Issue 2, pp. 695 - 711.
dc.identifier.urihttps://hdl.handle.net/2144/22006
dc.description.abstractStructured illumination microscopy (SIM) improves resolution by down-modulating high-frequency information of an object to fit within the passband of the optical system. Generally, the reconstruction process requires prior knowledge of the illumination patterns, which implies a well-calibrated and aberration-free system. Here, we propose a new algorithmic self-calibration strategy for SIM that does not need to know the exact patterns a priori, but only their covariance. The algorithm, termed PE-SIMS, includes a pattern-estimation (PE) step requiring the uniformity of the sum of the illumination patterns and a SIM reconstruction procedure using a statistical prior (SIMS). Additionally, we perform a pixel reassignment process (SIMS-PR) to enhance the reconstruction quality. We achieve 2× better resolution than a conventional widefield microscope, while remaining insensitive to aberration-induced pattern distortion and robust against parameter tuning.en_US
dc.description.urihttps://www.osapublishing.org/boe/abstract.cfm?uri=boe-8-2-695
dc.description.urihttps://arxiv.org/abs/1611.00287
dc.format.extentp. 695 - 711en_US
dc.languageeng
dc.relation.ispartofBiomed Opt Express
dc.rightsCopyright 2016 Optical Society of America. The accepted manuscript of this article is being made available in OpenBU under Boston University's open access policy.en_US
dc.subjectBlind deconvolutionen_US
dc.subjectSuperresolutionen_US
dc.subjectMicroscopyen_US
dc.subjectComputational imagingen_US
dc.subjectScience & technologyen_US
dc.subjectLife sciences & biomedicineen_US
dc.subjectBiochemical research methodsen_US
dc.subjectOpticsen_US
dc.subjectRadiology, nuclear medicineen_US
dc.subjectBiochemistry & molecular biologyen_US
dc.subjectPhase-shift estimationen_US
dc.subjectFluorescence microscopyen_US
dc.subjectSpeckle illuminationen_US
dc.subjectLateral superresolutionen_US
dc.subjectConfocal microscopyen_US
dc.subjectResolution limiten_US
dc.subjectExcitationen_US
dc.subjectAlgorithmen_US
dc.subjectMedical imagingen_US
dc.titleStructured illumination microscopy with unknown patterns and a statistical prioren_US
dc.typeArticleen_US
dc.description.versionAccepted manuscripten_US
dc.identifier.doi10.1364/BOE.8.000695
pubs.elements-sourcepubmeden_US
pubs.notesEmbargo: Not knownen_US
pubs.organisational-groupBoston Universityen_US
pubs.organisational-groupBoston University, College of Engineeringen_US
pubs.organisational-groupBoston University, College of Engineering, Department of Electrical & Computer Engineeringen_US
pubs.publication-statusPublished onlineen_US
dc.identifier.orcid0000-0002-1316-4456 (Tian, Lei)


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