000009405 001__ 9405
000009405 005__ 20240124114321.0
000009405 0247_ $$2DOI$$a10.6083/ws859g39n
000009405 037__ $$aETD
000009405 245__ $$aInstance and self-supervised learning-based image registration in RKHS
000009405 260__ $$bOregon Health and Science University
000009405 269__ $$a2021
000009405 336__ $$aDissertation
000009405 502__ $$bPh.D.
000009405 520__ $$aThis work introduces novel methods in the field of deformable image registration, both classical and learning-based. A central theme of the work is leveraging Reproducing Kernel Hilbert Space theory as a powerful regularization framework for dense displacement fields that are estimated via image registration.
000009405 542__ $$fIn copyright - single owner
000009405 650__ $$aAlgorithms$$014437
000009405 650__ $$aDeep Learning$$012734
000009405 650__ $$aCorrelation of Data$$012922
000009405 6531_ $$amachine intelligence
000009405 6531_ $$acomputer neural network
000009405 6531_ $$amedical imaging
000009405 691__ $$aSchool of Medicine$$041369
000009405 692__ $$aDepartment of Computer Science and Electrical Engineering$$041404
000009405 7001_ $$aAl Safadi, Ebrahim B.
000009405 8564_ $$990acde04-15ce-4311-aa53-64551c00237b$$s18525561$$uhttps://digitalcollections.ohsu.edu/record/9405/files/AlSafadi.Ebrahim.2021.pdf
000009405 905__ $$a/rest/prod/ws/85/9g/39/ws859g39n
000009405 909CO $$ooai:digitalcollections.ohsu.edu:9405$$pstudent-work
000009405 980__ $$aTheses and Dissertations