| Literature DB >> 24579119 |
Manasi Datar1, Ilwoo Lyu2, SunHyung Kim3, Joshua Cates4, Martin A Styner2, Ross Whitaker1.
Abstract
Establishing correspondence points across a set of biomedical shapes is an important technology for a variety of applications that rely on statistical analysis of individual subjects and populations. The inherent complexity (e.g. cortical surface shapes) and variability (e.g. cardiac chambers) evident in many biomedical shapes introduce significant challenges in finding a useful set of dense correspondences. Application specific strategies, such as registration of simplified (e.g. inflated or smoothed) surfaces or relying on manually placed landmarks, provide some improvement but suffer from limitations including increased computational complexity and ambiguity in landmark placement. This paper proposes a method for dense point correspondence on shape ensembles using geodesic distances to a priori landmarks as features. A novel set of numerical techniques for fast computation of geodesic distances to point sets is used to extract these features. The proposed method minimizes the ensemble entropy based on these features, resulting in isometry invariant correspondences in a very general, flexible framework.Entities:
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Year: 2013 PMID: 24579119 PMCID: PMC4156012 DOI: 10.1007/978-3-642-40763-5_3
Source DB: PubMed Journal: Med Image Comput Comput Assist Interv