Paper
7 February 2007 Richardson-Lucy deconvolution for two-photon fluorescence images via non-linear diffusion equation pre-filtering
Author Affiliations +
Abstract
Two-photon fluorescence microscopy is a powerful technique to obtain the stacks of neuronal individual or population morphologies deep inside brain tissue in vivo. However, the stacks often suffer from increasing noises with depth because of light scattering of specimen and optical distortion of microscopic system. Therefore, deconvolution becomes a more useful and a crucial approach to restore the original details of neuronal structure in fluorescence images. Since Richardson-Lucy deconvolution algorithm is appropriate for Poisson process of microscopy but sensitive to noise, we propose a scheme that it pre-filters noise via Perona-Malik nonlinear anisotropic diffusion before performing regularized Richardson-Lucy deconvolution algorithm. In contrast to other restoration approaches, the preliminary denoising of Perona-Malik diffusion model provides a better trade-off between noise reduction and edge preservation, and helps to following regularized Richardson-Lucy deconvolution procedure. Experimental results have shown that proposed scheme is effective and robust for restoring noisy two-photon fluorescence images.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hongmin Zhang, Zhitao Zhang, Qingming Luo, and Shaoqun Zeng "Richardson-Lucy deconvolution for two-photon fluorescence images via non-linear diffusion equation pre-filtering", Proc. SPIE 6436, Complex Dynamics and Fluctuations in Biomedical Photonics IV, 64360P (7 February 2007); https://doi.org/10.1117/12.701750
Lens.org Logo
CITATIONS
Cited by 2 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Deconvolution

Point spread functions

Luminescence

Diffusion

Microscopy

Two photon excitation microscopy

Anisotropic diffusion

Back to Top