Temporal focusing-based multiphoton excitation fluorescence images with background noise cancellation via Hilbert-Huang transform

Yvonne Yuling Hu, Yuan Rong Luo, Chun Yu Lin, Chia-Yuan Chang, Shean Jen Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Temporal 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 μm to 0.73 μm with structure frequency in 1.06 μm-1.

Original languageEnglish
Title of host publicationThree-Dimensional and Multidimensional Microscopy
Subtitle of host publicationImage Acquisition and Processing XXVI
EditorsTony Wilson, Thomas G. Brown
PublisherSPIE
ISBN (Electronic)9781510624085
DOIs
Publication statusPublished - 2019 Jan 1
EventThree-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI 2019 - San Francisco, United States
Duration: 2019 Feb 52019 Feb 7

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume10883
ISSN (Print)1605-7422

Conference

ConferenceThree-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI 2019
CountryUnited States
CitySan Francisco
Period19-02-0519-02-07

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Atomic and Molecular Physics, and Optics
  • Biomaterials
  • Radiology Nuclear Medicine and imaging

Fingerprint Dive into the research topics of 'Temporal focusing-based multiphoton excitation fluorescence images with background noise cancellation via Hilbert-Huang transform'. Together they form a unique fingerprint.

Cite this