Inverse-consistent surface mapping with laplace-beltrami eigen-features

Yonggang Shi, Jonathan H. Morra, Paul M. Thompson, Arthur W. Toga

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

39 Scopus citations


We propose in this work a novel variational method for computing maps between surfaces by combining informative geometric features and regularizing forces including inverse consistency and harmonic energy. To tackle the ambiguity in defining homologous points on smooth surfaces, we design feature functions in the data term based on the Reeb graph of the Laplace-Beltrami eigenfunctions to quantitatively describe the global geometry of elongated anatomical structures. For inverse consistency and robustness, our method computes simultaneously the forward and backward map by iteratively solving partial differential equations (PDEs) on the surfaces. In our experiments, we successfully mapped 890 hippocampal surfaces and report statistically significant maps of atrophy rates between normal controls and patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD).

Original languageEnglish
Title of host publicationInformation Processing in Medical Imaging - 21st International Conference, IPMI 2009, Proceedings
Number of pages12
StatePublished - 2009
Externally publishedYes
Event21st International Conference on Information Processing in Medical Imaging, IPMI 2009 - Williamsburg, VA, United States
Duration: 5 Jul 200910 Jul 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5636 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference21st International Conference on Information Processing in Medical Imaging, IPMI 2009
Country/TerritoryUnited States
CityWilliamsburg, VA


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