Rigid Registration of Echoplanar and Conventional Magnetic Resonance Images by Minimizing the Kullback-Leibler Distance.
Functional Magnetic Resonance Imaging (fMRI) studies are derived from a time series of Echo-Planar images (EPIs). Compared to conventional Magnetic Resonance Images (MRIs), EPIs are of relatively poor quality for discerning anatomic features and are often registered with corresponding MRIs to map brain activity to neuroanatomy. In this paper we demonstrate the utility of a technique to register an EPI-MRI pair by minimizing the discrepancy between its joint intensity probability mass function (PMF) and a previously learned one for a properly registered EPI-MRI pair, using the Kullback-Leibler Distance (KLD). In probing experiments Joint Entropy (JE) and Mutual Information showed significant bias relative to KLD along the axial direction and JE along a rotation axis. A comparison of searches using random starting poses showed KLD to have lower final pose errors than JE. Results of variation on parameters of the KLD based EPI-MRI registration technique are also presented.
MIT Artificial Intelligence Laboratory, Cambridge, MA USA.
Salil
S
Soman
Surgical Planning Laboratory, Brigham & Women's Hospital, Boston, MA USA.
Albert C S
AC
Chung
UMDNJ - Robert Wood Johnson Medical School, NJ USA.
W Eric L
WE
Grimson
Dept. of Computer Science, Hong Kong University of Science & Technology, HK.
William M
WM
Wells