English

FastGeodis: Fast Generalised Geodesic Distance Transform

Computer Vision and Pattern Recognition 2022-11-28 v2 Image and Video Processing

Abstract

The FastGeodis package provides an efficient implementation for computing Geodesic and Euclidean distance transforms (or a mixture of both), targeting efficient utilisation of CPU and GPU hardware. In particular, it implements the paralellisable raster scan method from Criminisi et al. (2009), where elements in a row (2D) or plane (3D) can be computed with parallel threads. This package is able to handle 2D as well as 3D data, where it achieves up to a 20x speedup on a CPU and up to a 74x speedup on a GPU as compared to an existing open-source library (Wang, 2020) that uses a non-parallelisable single-thread CPU implementation. The performance speedups reported here were evaluated using 3D volume data on an Nvidia GeForce Titan X (12 GB) with a 6-Core Intel Xeon E5-1650 CPU. Further in-depth comparison of performance improvements are discussed in the FastGeodis documentation: https://fastgeodis.readthedocs.io

Keywords

Cite

@article{arxiv.2208.00001,
  title  = {FastGeodis: Fast Generalised Geodesic Distance Transform},
  author = {Muhammad Asad and Reuben Dorent and Tom Vercauteren},
  journal= {arXiv preprint arXiv:2208.00001},
  year   = {2022}
}

Comments

Accepted at Journal of Open Source Software (JOSS)

R2 v1 2026-06-25T01:20:24.517Z