1. A method for synthesizing a base image data set and a match image data set into a single fused composite image data set with accurate registration and congruence using a programmable data processing system, comprising data input means, display means, and data storage means, the method comprising the steps of: (a) using the data input means to provide the programmable data processing system with the base image data set and the match image data set, the base image data set and the match image data set each comprising a biomedical image generated by a biomedical image generation means; (b) storing the base image data set and the match image data set in the data storage means; and (c) using the programmable data processing system to perform the steps of: (1) if the voxels of the base image data set are non-cubic, applying shape-based surface interpolation to interpolate intermediate contours between every consecutive pair of actual contours of the base image data set to obtain a smoothly varying surface; (2) uniformly sampling a plurality of registration points from the surface of the match image data set; (3) creating a distance image data set by performing a distance transformation to convert the surface of the base image data set into a grey-level image in which all voxels have a value corresponding to the distance to the nearest surface voxel; (4) transforming geometrically the registration points on the surface of the match image data set to become more closely aligned in orientation with corresponding points on the surface of the distance image data set; (5) calculating the value of a cost function between registration points on the surface of the match image data set and the corresponding points on the surface of the distance image data set; (6) if the value of the cost function is below a predetermined multi-level threshold value, reducing the threshold by at least one level and returning to step (4); (7) storing the value of the cost function with the corresponding values for the geometric transformation parameters for later comparison; (8) repeating steps (4) through (7) for each of a plurality of predetermined uniformly distributed starting points within the match image data set in order to generate a plurality of cost function values and corresponding geometric transformation parameters; (9) if the resolution of the base image data set and the match image data set is below a predetermined multi-level maximum resolution level, scaling the base image data set and the match image data set upward at least one level and returning to step (4); (10) selecting the minimum of the plurality of stored cost function values and using the corresponding stored geometric transformation parameters to map the match image data set onto the base image data set to create a single fused composite multi-valued image with two or more values associated with each 3-D spatial (x,y,z) coordinate uniquely representing and corresponding to the 3-D distribution of values of the base image data set and the match image data set; and (11) displaying, on the display means, the composite image values associated with each 3-D spatial (x,y,z) coordinate.