MUTUAL INFORMATION FOR AUTOMATED UNWARPING OF RAT-BRAIN AUTORADIOGRAPHS

An automated multimodal warping based on mutual information metric (MI ) as a mapping cost function is demonstrated. Mutual information (I) i s calculated from a two-dimensional (2D) gray scale histogram of an im age pair, and MI (= -I) provides a matching cost function which can be effective in registration of two- or three-dimensional data sets inde pendent of modality. Most histological image data, though information rich and high resolution, present nonlinear deformations due to the sp ecimen sectioning and need reconstitution into deformation-corrected v olumes prior to geometric mapping to an anatomical volume for spatial analyses. Section alignment via automatic 2D registrations employing M I as a global cost function and thin-plate-spline (TPS) warping is app lied to deoxy-D-[C-14]glucose autoradiographic image slices of a rat b rain with video reference images of the uncut block face to reconstitu te a cerebral glucose metabolic volume data. Unlike the traditional fe ature-based TPS warping algorithms, initial control points are defined independently from feature landmarks. Registration quality using auto mated multimodal image warping is validated by comparing MIs of the im age pair registered by automated affine registration and manual warpin g method. The MI proves to be a robust objective matching cost functio n effective for automatic multimodality warping for 2D data sets and c an be readily applied to volume registrations. (C) 1997 Academic Press .