Multi-view image fusion improves resolution in three-dimensional microscopy

Abstract

A non-blind, shift-invariant image processing technique that fuses multi-view three-dimensional image data sets into a single, high quality three-dimensional image is presented. It is effective for 1) improving the resolution and isotropy in images of transparent specimens, and 2) improving the uniformity of the image quality of partially opaque samples. This is demonstrated with fluorescent samples such as Drosophila melanogaster and Medaka embryos and pollen grains imaged by Selective Plane Illumination Microscopy (SPIM). The application of the algorithm to SPIM data yields high-resolution images of organ structure and gene expression, in some cases at a sub-cellular level, throughout specimens ranging from several microns up to a millimeter in size.