We present a robust, low-cost neural network-based optical autofocus system that can operate over a range of ±100μm with submicron precision, enabling automated high-content super-resolved imaging with a 1.3 NA objective lens.
Light sheet fluorescence microscopy (LSFM) enables fast 3D imaging of live cells, however the traditional LSFM geometry is not compatible with conventional multiwell plates used in high content microscopy.
We have developed an automated LSFM platereader based on an oblique plane microscope (OPM) that is compatible with multiwell plates. The system enables automated studies of cells cultured in a collagen matrix. Cells across 30 different conditions are imaged every 5 minutes for 12 hours. A custom 3D segmentation and tracking pipeline analyses cell morphological dynamics, allowing the study of a range of treatment conditions on the ability of cancer cells to change shape and invade.
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