Fluorescence Microscopic Image Three-dimensional Reconstruction Based on Space-variant Point Spread Function
- https://doi.org/10.2991/cnct-16.2017.74How to use a DOI?
- Fluorescence microscopic images, 3D reconstruction, Space-variant PSF, Cubic spline.
Three-dimensional (3D) reconstruction of fluorescence microscopic images is a challenging topic in the image processing, because the imaging system is very complex, and the point spread function (PSF) continuously varies along the optical axis. Generally, the more exact the PSF is, the higher the reconstruction accuracy is. An image reconstruction method is proposed for fluorescence microscopic sample based on space-variant PSF (SV-PSF) which is generated by cubic spline theory in this paper. Firstly, key PSFs are estimated by blind deconvolution algorithm at several depths of fluorescence microscopic image stack along the optical axis. Then, other PSFs are interpolated using cubic spline theory. Finally, a 3D microscopic specimen model is reconstructed by this group of SV-PSFs. The experimental results show that the proposed method is obviously superior to the method in which space-invariant (SI) PSF is used to reconstruct the simulated and real fluorescence microscopic images.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yu WANG AU - Na ZHANG AU - Huan JIANG PY - 2016/12 DA - 2016/12 TI - Fluorescence Microscopic Image Three-dimensional Reconstruction Based on Space-variant Point Spread Function BT - Proceedings of the International Conference on Computer Networks and Communication Technology (CNCT 2016) PB - Atlantis Press SP - 537 EP - 545 SN - 2352-538X UR - https://doi.org/10.2991/cnct-16.2017.74 DO - https://doi.org/10.2991/cnct-16.2017.74 ID - WANG2016/12 ER -