Paul C. Goodwin

Image reconstruction for structured-illumination microscopy with low signal level

We report a new image processing technique for the structured illumination microscopy designed to work with low signals, with the goal of reducing photobleaching and phototoxicity of the sample. Using a pre-filtering process to estimate experimental parameters and total variation as a constraint to reconstruct, we obtain two orders of magnitude of exposure reduction while maintaining the resolution improvement and image quality compared to a standard structured illumination microscopy. The algorithm is validated on both fixed and live cell data with results confirming that we can image more than 15x more time points compared to the standard technique.

Microscopy, Immuno-Histochemistry, Digital Imaging, and Quantitative Microscopy

Abstract Advances in microscopy including improvements in objectives, light sources, computational power, and digital cameras, with the ability to obtain images of regions of interest or whole slides, have led to the resurgence of the light microscope in biomedical research. Similarly, advances in immunohistochemistry (IHC), such as heat-induced epitope retrieval, have increased the use of this technique to obtain important information about specific molecules in tissues. Finally, advances in digital pathology and software programs that objectively analyze digital images has resulted in the increased use of quantitative microscopy—either stereology or image analysis—to efficiently obtain data from studies using histopathology or IHC. The goal of this chapter is to provide the fundamental information required to successfully use microscopy, IHC, and quantitative microscopy to obtain objective nonbiased data from histology sections.