Depth-variant deconvolution of 3D widefield fluorescence microscopy using the penalized maximum likelihood estimation method

Jeongtae Kim, Suhyeon An, Sohyun Ahn, Boyoung Kim

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

We investigated the deconvolution of 3D widefield fluorescence microscopy using the penalized maximum likelihood estimation method and the depth-variant point spread function (DV-PSF). We build the DVPSF by fitting a parameterized theoretical PSF model to an experimental microbead image. On the basis of the constructed DV-PSF, we restore the 3D widefield microscopy by minimizing an objective function consisting of a negative Poisson likelihood function and a total variation regularization function. In simulations and experiments, the proposed method showed better performance than existing methods.

Original languageEnglish
Pages (from-to)27668-27681
Number of pages14
JournalOptics Express
Volume21
Issue number23
DOIs
StatePublished - 18 Nov 2013

Fingerprint

Dive into the research topics of 'Depth-variant deconvolution of 3D widefield fluorescence microscopy using the penalized maximum likelihood estimation method'. Together they form a unique fingerprint.

Cite this