Robust shape correspondence via spherical patch matching for atlases of partial skull models

Boris A. Gutman, Ryan McComb, Jay Sung, Won Moon, Paul M. Thompson

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

2 Scopus citations

Abstract

Problems of dense partial correspondence for meshes of variable topology are ubiquitous in medical imaging. In particular, this problem arises when constructing average shapes and probabilistic atlases of partial skull models. We exploit the roughly spherical extrinsic geometry of the skull to first approximate skull models with shapes of spherical topology. The skulls are then matched parametrically via a non-local non-linear landmark search using normalized spherical cross-correlation of curvature features. A dense spherical registration algorithm is then applied for a final correspondence. We show that the non-local step is crucial for accurate mappings. We apply the entire pipeline to low SNR skull meshes extracted from conical CT images. Our results show that the approach is robust for creating averages for families of shapes that deviate significantly from local isometry.

Original languageEnglish
Title of host publicationMesh Processing in Medical Image Analysis - MICCAI 2012 International Workshop, MeshMed 2012, Proceedings
Pages89-100
Number of pages12
DOIs
StatePublished - 2012
Externally publishedYes
EventMICCAI 2012 International Workshop on Mesh Processing in Medical Image Analysis, MeshMed 2012 - Nice, France
Duration: 1 Oct 20121 Oct 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7599 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceMICCAI 2012 International Workshop on Mesh Processing in Medical Image Analysis, MeshMed 2012
Country/TerritoryFrance
CityNice
Period1/10/121/10/12

Keywords

  • Patch Matching
  • Shape Atlas
  • Shape Registration
  • Spherical Cross Correlation

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