Artificial intelligence and registration of functional and structural images: generalised 2D approaches

A 2D relational image matching/fusion algorithm is introduced. It is implemented in the domain of medical imaging and is based on artificial intelligence (AI) paradigms-in particular, knowledge base representation and tree search. The 2D reference and target images are selected from 3D sets and are segmented into nontouching and nonoverlapping regions, using iterative thresholding and/or knowledge about the anatomical shapes of human organs. Selected image region attributes are calculated. Region matches are obtained using a tree search, and the error is minimized by evaluating a “goodness of matching” function based on similarities of region attributes. Once the matched regions are found and the spline geometric transform is applied to regional centres of gravity, images are ready for fusion into a single 2D image of higher clarity