Medical image matching-a review with classification

Pol, E.-J.D.; Viergever, M.A.; van den Elsen, P.A.

doi:10.1109/51.195938

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Medical image matching-a review with classification

Author(s): P.A. van den Elsen , E.-J.D. Pol , M.A. Viergever

Publication date (Print): March 1993

Journal: IEEE Engineering in Medicine and Biology Magazine

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

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Least-squares fitting of two 3-d point sets.

K. Arun, T S Huang, S. Blostein (1987)

Two point sets {pi} and {p'i}; i = 1, 2,..., N are related by p'i = Rpi + T + Ni, where R is a rotation matrix, T a translation vector, and Ni a noise vector. Given {pi} and {p'i}, we present an algorithm for finding the least-squares solution of R and T, which is based on the singular value decomposition (SVD) of a 3 × 3 matrix. This new algorithm is compared to two earlier algorithms with respect to computer time requirements.