Simultaneous usage of homologous points, lines, and planes for optimal, 3-D, linear registration of multimodality imaging data

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Abstract
The authors have extended point-based registration to include simultaneous registration of points, lines, and planes, to permit accurate and easily implemented three-dimensional (3-D) registration of multimodal data sets for fusion of clinical anatomic and functional imaging modalities. Constructive geometry is used to define user-identified features where each feature's role in the reconstruction is weighted based on its relative statistical quality, i.e., variance. The algorithm employs singular value decomposition (SVD) and optimization techniques to find the minimum weighted least mean square error (LMSE) affine solution. The new method is generally more accurate due to the availability of more features to register. Notably the error surface contains only one minimum. Different subclasses of affine solutions can be obtained based on appropriateness and sufficiency of the number and type of input features. Preliminary results indicate that this method is useful in multimodal diagnostic image fusion.