Three dimensional image alignment, registration and fusion.
Combined assessment of three dimensional anatomical and functional images (SPECT, PET, MRI, CT) is useful to determine the nature and extent of lesions in many parts of the body. Physicians principally rely on their spatial sense to mentally re-orient and overlap images obtained with different imaging modalities. Objective methods that enable easy and intuitive image registration can help the physician arrive at more optimal diagnoses and better treatment decisions. This review describes a simple, intuitive and robust image registration approach developed in our laboratory. It differs from most other registration techniques in that it allows the user to incorporate all of the available information within the images in the registration process. This method takes full advantage of the ability of knowledgeable operators to achieve image registration and fusion using an intuitive interactive visual approach. It can register images accurately and quickly without the use of elaborate mathematical modeling or optimization techniques. The method provides the operator with tools to manipulate images in three dimensions, including visual feedback techniques to assess the accuracy of registration (grids, overlays, masks, and fusion of images in different colors). Its application is not limited to brain imaging and can be applied to images from any region in the body. The overall effect is a registration algorithm that is easy to implement and can achieve accuracy on the order of one pixel.
Division of Nuclear Medicine, Children's Hospital, Harvard Medical School, Boston, MA 02115, USA.
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Treves
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Mitchell
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Habboush
D000465:Algorithms; D001921:Brain / Q000473:pathology; D001932:Brain Neoplasms / Q000175:diagnosis; D002648:Child; D004827:Epilepsy / Q000175:diagnosis; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D009072:Moyamoya Disease / Q000175:diagnosis; D014055:Tomography, Emission-Computed; D015899:Tomography, Emission-Computed, Single-Photon