Multi-object geodesic active contours (MOGAC)

Blake C. Lucas, Michael Kazhdan, Russell H. Taylor

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

9 Scopus citations


An emerging topic is to build image segmentation systems that can segment hundreds to thousands of objects (i.e. cell segmentation \ tracking, full brain parcellation, full body segmentation, etc.). Multi-object Level Set Methods (MLSM) perform this task with the benefit of sub-pixel precision. However, current implementations of MLSM are not as computationally or memory efficient as their region growing and graph cut counterparts which lack sub-pixel precision. To address this performance gap, we present a novel parallel implementation of MLSM that leverages the sparse properties of the algorithm to minimize its memory footprint for multiple objects. The new method, Multi-Object Geodesic Active Contours (MOGAC), can represent N objects with just two functions: a label mask image and unsigned distance field. The time complexity of the algorithm is shown to be O((M^d)/P) for M^d pixels and P processing units in dimension d={2,3}, independent of the number of objects. Results are presented for 2D and 3D image segmentation problems.

Original languageEnglish (US)
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - MICCAI2012 - 15th International Conference, Proceedings
EditorsAlbert Montillo, Bjoern H. Menze, Le Lu, Georg Langs, Antonio Criminisi, Bjoern H. Menze, Nicholas Ayache, Hervé Delingette, Zhuowen Tu, Georg Langs, Polina Golland, Kensaku Mori
PublisherSpringer Verlag
Number of pages9
ISBN (Print)9783642334177
StatePublished - 2012
Event15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012 - Nice, France
Duration: Oct 5 2012Oct 5 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7511 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012


  • Active contours
  • Level set
  • Parallel
  • Segmentation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Multi-object geodesic active contours (MOGAC)'. Together they form a unique fingerprint.

Cite this