RegFus: A toolbox for distributed multi-view image registration and fusion

Multi-view and multi-tile light (sheet) microscopy techniques produce large image datasets that are unaligned in space, time and channels. We present a collection of algorithm implementations and scripts to register and fuse such datasets in 2-5d, including e.g. group registration and multi-view deconvolution. Based on the scientific python stack and leveraging dask for chunked and distributed image processing, RegFus enables the efficient reconstruction of large multi-view datasets with low memory requirements, allowing to make use of GPUs and distributed computing. Visualization in napari helps to guide and troubleshoot the reconstruction process.</p