Deconvolution is a well-known image processing technique used to help overcome the limitations of diffraction by increasing the resolution and contrast of fluorescence microscopy, but has traditionally been too slow for use in parallel with image acquisition and is instead relegated to post-processing of chosen subsets. Here we’ll showcase CUDA-accelerated Richardson Lucy-based 3D deconvolution software that can run in near real time, permitting deconvolution to be integrated with image acquisition. Such an integration improves high speed microscopy and high content screening by improving image resolution while decreasing the needed light intensity. We will highlight the practical applications of deconvolution applied to examples from instruments such as lattice light sheet, spinning disk confocal, and the Akoya CODEX technology.

The CODEX Technology, originally developed in the lab of Dr. Garry Nolan at Stanford University, is used to analyze biological tissues at an unprecedented level of complexity. In this webinar, we will present the CODEX System including the complex analysis methods Akoya has developed to turn raw image data into biologically interpretable information.

• The basics of how deconvolution aids fluorescence microscopy

• Examples of the practical applications of deconvolution from individual instruments to big clusters

• Novel methods for generating ultra-high plex tissue imaging

• Image analysis methods to characterize complex cancer and other disease tissues

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