Image segmentation for sets of objects

Abstract

A computing system may generate an initial segmentation mask by applying a neural network to a 3D image of a set of objects. The initial segmentation mask associates voxels of the 3D image with individual objects of the set of objects. Additionally, the computing system generates a refined segmentation mask. As part of generating the refined segmentation mask, the computing system performs, for each respective object, a front propagation process for the respective object. The front propagation process for the respective object uses input voxel data to relabel, in the refined segmentation mask, voxels of the 3D image as being associated with the respective object. A stopping condition of a path evaluated by the front propagation process for the respective object occurs when the front propagation process evaluates a voxel identified in the initial segmentation mask as being associated with a different one of the objects from the respective object.