Image registration using stationary velocity fields parameterized by norm-minimizing Wendland kernel

Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

Interpolating kernels are crucial to solving a stationary velocity field (SVF) based image registration problem. This is because, velocity fields need to be computed in non-integer locations during integration. The regularity in the solution to the SVF registration problem is controlled by the regularization term. In a variational formulation, this term is traditionally expressed as a squared norm which is a scalar inner product of the interpolating kernels parameterizing the velocity fields. The minimization of this term using the standard spline interpolation kernels (linear or cubic) is only approximative because of the lack of a compatible norm. In this paper, we propose to replace such interpolants with a norm-minimizing interpolant - the Wendland kernel which has the same computational simplicity like B-Splines. An application on the Alzheimer's disease neuroimaging initiative showed that Wendland SVF based measures separate (Alzheimer's disease v/s normal controls) better than both B-Spline SVFs (p<0.05 in amygdala) and B-Spline freeform deformation (p<0.05 in amygdala and cortical gray matter).
TitelMedical Imaging 2015: Image Processing
Antal sider7
ForlagSPIE - International Society for Optical Engineering
StatusUdgivet - 2015
BegivenhedSPIE Medical Imaging, 2015 - Orlando, FL, USA
Varighed: 21 feb. 201526 feb. 2015


KonferenceSPIE Medical Imaging, 2015
ByOrlando, FL
NavnProceedings of S P I E - International Society for Optical Engineering

ID: 256217837