Richardson-Lucy deconvolution for super-resolution imaging in a confocal microscope with programmable illumination

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dc.contributor.advisorMontes Usategui, Mario
dc.contributor.authorTrofymchuk, Artem
dc.date.accessioned2021-10-05T17:25:41Z
dc.date.available2021-10-05T17:25:41Z
dc.date.issued2021-02
dc.descriptionTreballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2021, Tutor: Mario Montes Usateguica
dc.description.abstractI have tried a Richardson-Lucy deconvolution algorithm with a simulator of a programmable illumination laser microscope coded in Python for different excitation patterns, concluding that the most resolutive optimization process is for the multi point mode scanning, achieving a resolution below 100nm for a simulated noisy imageca
dc.format.extent5 p.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/2445/180388
dc.language.isoengca
dc.rightscc-by-nc-nd (c) Trofymchuk, Trofymchuk
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceTreballs Finals de Grau (TFG) - Física
dc.subject.classificationAlgorisme Richardson–Lucycat
dc.subject.classificationMicroscopi confocalcat
dc.subject.classificationTreballs de fi de graucat
dc.subject.otherRichardson–Lucy algorithmeng
dc.subject.otherConfocal microscopyeng
dc.subject.otherBachelor's theseseng
dc.titleRichardson-Lucy deconvolution for super-resolution imaging in a confocal microscope with programmable illuminationeng
dc.typeinfo:eu-repo/semantics/bachelorThesisca

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