Paper
28 January 2015 Non-rigid image registration under non-deterministic deformation bounds
Qian Ge, Namita Lokare, Edgar Lobaton
Author Affiliations +
Proceedings Volume 9287, 10th International Symposium on Medical Information Processing and Analysis; 92870T (2015) https://doi.org/10.1117/12.2072530
Event: Tenth International Symposium on Medical Information Processing and Analysis, 2014, Cartagena de Indias, Colombia
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.
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Qian Ge, Namita Lokare, and Edgar Lobaton "Non-rigid image registration under non-deterministic deformation bounds ", Proc. SPIE 9287, 10th International Symposium on Medical Information Processing and Analysis, 92870T (28 January 2015); https://doi.org/10.1117/12.2072530
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KEYWORDS
Image registration

Brain mapping

Brain

Error analysis

Image analysis

Statistical analysis

Medical imaging

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