title: Automated registration of multimodal brain image sets using computer vision methods.
abstract: We present a new method of registering three dimensional image volumes of the brain of a given patient acquired at different times or with different imaging modalities, or both. Registration is an essential requirement for fusing the data from the two image sets so as to either increase the available information by exploiting complementary imaging modalities, or to measure small changes over time for prognostication, disease assessment, etc. The new technique exploits an external, removable, remountable reference frame which is attached to the head. Computer vision techniques are used to determine the positions of fiducial marks in every image. The transformation required to map each image of one image volume onto the other image volume is developed using the theory of quaternions. The results indicate that the new technique is robust and practical in a clinical setting.
authors.affiliation: Department of Electrical and Computer Engineering, DalTech, Dalhousie University, Halifax, NS, Canada.
authors.forename: G
authors.initials: G
authors.lastname: Secretta
authors.forename: P H
authors.initials: PH
authors.lastname: Gregson
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology* / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D008279:Magnetic Resonance Imaging; D008962:Models, Theoretical; D011187:Posture; D015203:Reproducibility of Results; D012399:Rotation; D013238:Stereotaxic Techniques; D015899:Tomography, Emission-Computed, Single-Photon