A work-efficient GPU algorithm for level set segmentation

Mike Roberts, Mario Costa Sousa, Joseph Ross Mitchell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations


We present a novel GPU level set segmentation algorithm that is both work-efficient and step-efficient. Our algorithm has O(log n) step-complexity, in contrast to previous GPU algorithms [Lefohn et al. 2004; Jeong et al. 2009] which have O(n) step-complexity. Moreover our algorithm limits the active computational domain to the minimal set of changing elements by examining both the temporal and spatial derivatives of the level set field. We apply our algorithm to 3D medical images (Figure 1) and demonstrate that our algorithm reduces the total number of processed level set field elements by 16× and is 14× faster than previous GPU algorithms with no reduction in segmentation accuracy.

Original languageEnglish (US)
Title of host publicationACM SIGGRAPH 2010 Posters, SIGGRAPH '10
StatePublished - 2010
EventACM SIGGRAPH 2010 Posters, SIGGRAPH '10 - Los Angeles, CA, United States
Duration: Jul 26 2010Jul 30 2010

Publication series

NameACM SIGGRAPH 2010 Posters, SIGGRAPH '10


OtherACM SIGGRAPH 2010 Posters, SIGGRAPH '10
Country/TerritoryUnited States
CityLos Angeles, CA

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Software


Dive into the research topics of 'A work-efficient GPU algorithm for level set segmentation'. Together they form a unique fingerprint.

Cite this