Improved methods for image registration.
We report a system for PET-MRI registration that is improved or optimized in several areas: (1) Automatic scalp/brain segmentation replaces manual drawing operations, (2) a new fast and accurate method of image registration, (3) visual assessment of registration quality is enhanced by composite imaging methods (i.e., fusion) and (4) the entire procedure is embedded in a commercially available scientific visualization package, thereby providing a consistent graphical user interface. The segmentation algorithm was tested on 17 MRI data sets and was successful in all cases. Accuracy of image registration was equal to that of the Woods algorithm, but 10 times faster for PET-PET and 4 times faster for PET-MRI. The image fusion method allows detection of misalignments on the order of 2-3 mm. These results demonstrate an integrated system for intermodality image registration, which is important because the procedure can be performed by technicians with no anatomic knowledge and reduces the required time from hours to about 15 min on a modern computer workstation.
Alpert
N M
NM
PET Imaging Laboratory, Massachusetts General Hospital, Boston 02114, USA.
Berdichevsky
D
D
Levin
Z
Z
Morris
E D
ED
Fischman
A J
AJ
D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D001931:Brain Mapping / Q000295:instrumentation*; D003199:Computer Systems; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation*; D008279:Magnetic Resonance Imaging / Q000295:instrumentation*; D012016:Reference Values; D012984:Software; D014055:Tomography, Emission-Computed / Q000295:instrumentation*