3-DIMENSIONAL MULTIMODALITY MEDICAL IMAGE REGISTRATION USING A PARAMETER ACCUMULATION APPROACH

A parameter accumulation method based on the Hough transformation is p roposed to register three-dimensional (3-D) multimodality medical imag es. The estimation of registration parameters is decomposed into separ ate estimations of rotation, using directional vectors, and translatio n, using positional vectors. Similarly, the rotation parameters are de composed into the rotation axis and angle, which are then estimated se parately. This kind of decomposition reduces the parametric dimension and improves the computing efficiency which has been a major concern i n implementing the Hough transformation. When 3-D rotation is involved , evaluating registration error is not straightforward. This paper int roduces an equivalent error angle as a criterion to evaluate the perfo rmance of 3-D registration methods. Experimental results indicate that a least-squares fitting is superior to the parameter accumulation wit h data contaminated by additive noise only. When mismatched feature po ints (outliers) exist in the data set, however, the parameter accumula tion approach is more accurate. The application of the proposed approa ch to the registration of 3-D PET and CT images is demonstrated. (C) 1 996 American Association of Physicists in Medicine.