SuRVoS2
Once a dataset has been reconstructed into a 3D volume from the 2D images of microscopy samples, the next step is to annotate and segment the data to extract meaning from it. SuRVoS2 is a collection of tools to help accelerate annotation and segmentation of large volumetric bio-imaging workflows. It enables either shallow or deep machine learning approaches, using a suite of image processing filters, supervoxels (boundary adherent groupings of similar, adjacent voxels), and annotation hierarchies, including volume-segmantics. SuRVoS2 also provides a set of tools to enable visualization and interaction with large numbers of distributed annotations (e.g. those performed by multiple members of a group or citizen scientists).
