Real-time multi-view deconvolution
This addresses a critical delay in imaging pipelines for biological research, though it is incremental as it optimizes an existing method.
The paper tackled the bottleneck of slow multi-view deconvolution in light-sheet microscopy by enabling real-time processing, achieving a speed-up that matches acquisition time.
In light-sheet microscopy, overall image content and resolution are improved by acquiring and fusing multiple views of the sample from different directions. State-of-the-art multi-view (MV) deconvolution employs the point spread functions (PSF) of the different views to simultaneously fuse and deconvolve the images in 3D, but processing takes a multiple of the acquisition time and constitutes the bottleneck in the imaging pipeline. Here we show that MV deconvolution in 3D can finally be achieved in real-time by reslicing the acquired data and processing cross-sectional planes individually on the massively parallel architecture of a graphics processing unit (GPU).