Blind deconvolution of 3D fluorescence microscopy using depth-variant asymmetric PSF.

The 3D wide-field fluorescence microscopy suffers from depth-variant asymmetric blur. The depth-variance and axial asymmetry are due to refractive index mismatch between the immersion and the specimen layer. The radial asymmetry is due to lens imperfections and local refractive index inhomogeneities in the specimen. To obtain the PSF that has these characteristics, there were PSF premeasurement trials. However, they are useless since imaging conditions such as camera position and refractive index of the specimen are changed between the premeasurement and actual imaging. In this article, we focus on removing unknown depth-variant asymmetric blur in such an optical system under the assumption of refractive index homogeneities in the specimen. We propose finding few parameters in the mathematical PSF model from observed images in which the PSF model has a depth-variant asymmetric shape. After generating an initial PSF from the analysis of intensities in the observed image, the parameters are estimated based on a maximum likelihood estimator. Using the estimated PSF, we implement an accelerated GEM algorithm for image deconvolution. Deconvolution result shows the superiority of our algorithm in terms of accuracy, which quantitatively evaluated by FWHM, relative contrast, standard deviation values of intensity peaks and FWHM. Microsc. Res. Tech. 79:480-494, 2016.