The long-term objective is to develop a commercial software product to improve the resolution of 3D specimens imaged using differential interference contrast (DIC) microscopy and optical sectioning. This is achieved by reconstructing the relative refractive index distribution (or optical thickness) of a transparent 3D specimen and correcting for optical distortions in the lateral and axial directions. This resolution improvement is expected to allow sub-cellular components of sizes that are near, or just below, the diffraction limit to be resolved. Among other advantages, this will also enable the dry mass distribution in the object to be quantified, and for the reconstructed data to be used with standard 3D visualization methods or automated cell analysis. The Phase 1 of this project aims to collect 3D DIC images of specimens using optical sectioning, and process the data using an iterative image reconstruction algorithm. Parameters necessary to characterize the ideal DIC point spread function (PSF) will be estimated directly from the raw data, and the distortion introduced by the microscope optics will be accounted for using blind deconvolution. The highly nonlinear image formation process will be simplified (linearized) to minimize the computing resources required while maintaining the qualitative and quantitative accuracy of the reconstruction.
DIC microscopy is a very popular imaging modality, especially in the life sciences for observing living specimens. Many of the structures of interest are near or below the current resolution of the microscope, so the ability to increase the resolution is highly desirable. Reconstructing the relative refractive index distribution will allow quantifiable measurements, such as dry mass, to be made, and for the images to be interpreted without the inherent shadow-cast effect. The software is expected to be at least as popular as deconvolution used with other 3D imaging methods, such as wide-field fluorescence. The use of deconvolution with other 3D imaging methods, such as wide-field fluorescence, is gaining popularity. It is expected that this software will become as popular.
