FastGeodis: Fast Generalised Geodesic DistanceTransform
Muhammad Asad, Reuben Dorent, Tom Vercauteren
Abstract
Geodesic and Euclidean distance transforms have been widely used in a number of applications where distance from a set of reference points is computed. Methods from recent years have shown effectiveness in applying the Geodesic distance transform to interactively annotate 3D medical imaging data The Geodesic distance transform enables providing segmentation labels, i.e., voxel-wise labels, for different objects of interests. Despite existing methods for efficient computation of the Geodesic distance transform on GPU and CPU devices On the contrary, efficient methods for the computation of the Euclidean distance transform (Felzenszwalb & Huttenlocher, 2012) have open-source implementations Existing libraries, e.g., Wang (2020), provide C++ implementations of the Geodesic distance transform; however, they lack efficient utilisation of the underlying hardware and hence result in significant computation time, especially when applying them on 3D medical imaging volumes.