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dc.contributor.authorHu, Yvonne Yulingen_US
dc.contributor.authorLuo, Yuan-Rongen_US
dc.contributor.authorLin, Chun-Yuen_US
dc.contributor.authorChang, Chia-Yuanen_US
dc.contributor.authorChen, Shean-Jenen_US
dc.date.accessioned2019-10-05T00:09:46Z-
dc.date.available2019-10-05T00:09:46Z-
dc.date.issued2019-01-01en_US
dc.identifier.isbn978-1-5106-2409-2en_US
dc.identifier.issn0277-786Xen_US
dc.identifier.urihttp://dx.doi.org/10.1117/12.2507695en_US
dc.identifier.urihttp://hdl.handle.net/11536/152947-
dc.description.abstractTemporal focusing multiphoton excitation microscopy has wide field-of-view and optical sectioning. By using digital micromirror device, it provides patterned illumination. However, without filling the back aperture of objective lens, the axial confinement is limited to micron-meters, leading the out-of-focus fluorophores excited and image blurred. In this study, Hilbert-Huang transform is proposed to reduce the background noise. The empirical mode decomposition is first applied to disassemble the image into intrinsic mode functions and then reconstruct by Hilbert transform after diminishing background residues. The axial confinement can be enhanced from 2.79 mu m to 0.73 mu m with structure frequency in 1.06 mu m(-1).en_US
dc.language.isoen_USen_US
dc.subjectTemporal focusingen_US
dc.subjectDigital micromirror deviceen_US
dc.subjectStructured illumination microscopyen_US
dc.subjectHilbert-Huang transformen_US
dc.titleTemporal focusing-based multiphoton excitation fluorescence images with background noise cancellation via Hilbert-Huang transformen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1117/12.2507695en_US
dc.identifier.journalTHREE-DIMENSIONAL AND MULTIDIMENSIONAL MICROSCOPY: IMAGE ACQUISITION AND PROCESSING XXVIen_US
dc.citation.volume10883en_US
dc.citation.spage0en_US
dc.citation.epage0en_US
dc.contributor.department影像與生醫光電研究所zh_TW
dc.contributor.departmentInstitute of Imaging and Biomedical Photonicsen_US
dc.identifier.wosnumberWOS:000483011000016en_US
dc.citation.woscount0en_US
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