Multi-modal volume registration by maximization of mutual information.
A new information-theoretic approach is presented for finding the registration of volumetric medical images of differing modalities. Registration is achieved by adjustment of the relative position and orientation until the mutual information between the images is maximized. In our derivation of the registration procedure, few assumptions are made about the nature of the imaging process. As a result the algorithms are quite general and can foreseeably be used with a wide variety of imaging devices. This approach works directly with image data; no pre-processing or segmentation is required. This technique is, however, more flexible and robust than other intensity-based techniques like correlation. Additionally, it has an efficient implementation that is based on stochastic approximation. Experiments are presented that demonstrate the approach registering magnetic resonance (MR) images with computed tomography (CT) images, and with positron-emission tomography (PET) images. Surgical applications of the registration method are described.
Wells
W M
WM
Harvard Medical School, Department of Radiology, Boston, MA, USA. sw@ai.mit.edu
Viola
P
P
Atsumi
H
H
Nakajima
S
S
Kikinis
R
R
D001921:Brain / Q000473:pathology; D001932:Brain Neoplasms / Q000175:diagnosis* / Q000601:surgery; D003198:Computer Simulation; D005910:Glioma / Q000175:diagnosis / Q000601:surgery; D006801:Humans; D007257:Information Theory; D008279:Magnetic Resonance Imaging; D008577:Meningeal Neoplasms / Q000175:diagnosis / Q000601:surgery; D008579:Meningioma / Q000175:diagnosis / Q000601:surgery; D015203:Reproducibility of Results; D014055:Tomography, Emission-Computed; D014057:Tomography, X-Ray Computed