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Proceedings Paper

Non-rigid image registration under non-deterministic deformation bounds
Author(s): Qian Ge; Namita Lokare; Edgar Lobaton
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Paper Abstract

Image registration aims to identify the mapping between corresponding locations in an anatomic structure. Most traditional approaches solve this problem by minimizing some error metric. However, they do not quantify the uncertainty behind their estimates and the feasibility of other solutions. In this work, it is assumed that two images of the same anatomic structure are related via a Lipschitz non-rigid deformation (the registration map). An approach for identifying point correspondences with zero false-negative rate and high precision is introduced under this assumption. This methodology is then extended to registration of regions in an image which is posed as a graph matching problem with geometric constraints. The outcome of this approach is a homeomorphism with uncertainty bounds characterizing its accuracy over the entire image domain. The method is tested by applying deformation maps to the LPBA40 dataset.

Paper Details

Date Published: 28 January 2015
PDF: 10 pages
Proc. SPIE 9287, 10th International Symposium on Medical Information Processing and Analysis, 92870T (28 January 2015); doi: 10.1117/12.2072530
Show Author Affiliations
Qian Ge, North Carolina State Univ. (United States)
Namita Lokare, North Carolina State Univ. (United States)
Edgar Lobaton, North Carolina State Univ. (United States)


Published in SPIE Proceedings Vol. 9287:
10th International Symposium on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore, Editor(s)

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