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논문 기본 정보

자료유형
학술저널
저자정보
Jing Ren (University of Ontario Institute of Technology) Mark Green (University of Ontario Institute of Technology) Xishi Huang (Istuary Innovation Group) Anwar Abdalbari (University of Ontario Institute of Technology)
저널정보
대한의용생체공학회 Biomedical Engineering Letters (BMEL) Biomedical Engineering Letters (BMEL) Vol.7 No.2
발행연도
2017.1
수록면
173 - 181 (9page)

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초록· 키워드

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In this paper, we extend our previous work ondeformable image registration to inhomogenous tissues. Inhomogenous tissues include the tissues with embeddedtumors, which is common in clinical applications. It is avery challenging task since the registration method thatworks for homogenous tissues may not work well withinhomogenous tissues. The maximum error normallyoccurs in the regions with tumors and often exceeds theacceptable error threshold. In this paper, we propose a newerror correction method with adaptive weighting to reducethe maximum registration error. Our previous fastdeformable registration method is used in the inner loop. We have also proposed a new evaluation metric averageerror of deformation field (AEDF) to evaluate the registrationaccuracy in regions between vessels and bifurcationpoints. We have validated the proposed method using liverMR images from human subjects. AEDF results show thatthe proposed method can greatly reduce the maximumregistration errors when compared with the previousmethod with no adaptive weighting. The proposed methodhas the potential to be used in clinical applications toreduce registration errors in regions with tumors.

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