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Discriminative Sliding Preserving Regularization in Medical Image Registration

dc.contributor.authorRuan, Danen_US
dc.contributor.authorEsedoglu, Selimen_US
dc.contributor.authorFessler, Jeffrey A.en_US
dc.date.accessioned2011-08-18T18:21:18Z
dc.date.available2011-08-18T18:21:18Z
dc.date.issued2009-06-28en_US
dc.identifier.citationRuan, D.; Esedoglu, S.; Fessler, J.A. (2009). "Discriminative Sliding Preserving Regularization in Medical Image Registration." IEEE International Symposium on Biomedical Imaging: From Nano to Macro: 430-433. <http://hdl.handle.net/2027.42/85988>en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/85988
dc.description.abstractSliding effects often occur along tissue/organ boundaries. For instance, it is widely observed that the lung and diaphragm slide against the rib cage and the atria during breathing. Conventional homogeneous smooth registration methods fail to address this issue. Some recent studies preserve motion discontinuities by either using joint registration/segmentation or utilizing robust regularization energy on the motion field. However, allowing all types of discontinuities is not strict enough for physical deformations. In particular, flows that generate local vacuums or mass collisions should be discouraged by the energy functional. In this study, we propose a regularization energy that encodes a discriminative treatment of different types of motion discontinuities. The key idea is motivated by the Helmholtz-Hodge decomposition, and regards the underlying motion flow as a superposition of a solenoidal component, an irrotational component and a harmonic part. The proposed method applies a homogeneous penalty on the divergence, discouraging local volume change caused by the irrotational component, thus avoiding local vacuum or collision; it regularizes the curl field with a robust functional so that the resulting solenoidal component vanishes almost everywhere except on a singular set where the large shear values are preserved. This singularity set corresponds to sliding interfaces. Preliminary tests with both simulated and clinical data showed promising results.en_US
dc.publisherIEEEen_US
dc.titleDiscriminative Sliding Preserving Regularization in Medical Image Registrationen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelBiomedical Engineeringen_US
dc.subject.hlbtoplevelEngineeringen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationotherStanford University, Stanford, CA.en_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/85988/1/Fessler242.pdf
dc.identifier.doi10.1109/ISBI.2009.5193076en_US
dc.identifier.sourceIEEE International Symposium on Biomedical Imaging: From Nano to Macroen_US
dc.owningcollnameElectrical Engineering and Computer Science, Department of (EECS)


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