Tile-based Lucy-Richardson Deconvolution Modelling a Spatially-Varying PSF for Fast Multiview Fusion of Microscopical Images

Abstract: A framework for fast multiview fusion of Single Plane Illumination Microscopy (SPIM) images based on a spatially-variant point spread function (PSF) model recorded using fluorescent point markers (beads) inserted into the surrounding medium is presented. The beads are used for the registration of the images as well as for the estimation of the spatially-varying PSF function. A new fusion algorithm based on regularized Lucy-Richardson deconvolution and the Overlap-Save method (LRMOS-TV) is presented and tested on SPIM images. Our framework proposes a method of decomposing the image into small packages thus saving memory space and allowing for parallel processing. As to our knowledge this is the first framework allowing modeling of spatially-variant PSF functions for SPIM images.