Markers Registration in Image-Guided Surgery

Points automatic matching algorithm between image space and surgical space is proposed. The sorted distances between one marker and the rest construct a vector, called multidimensional distances vector(MDV) of the marker. By comparing the correlation coefficient of MDV, one marker in image space can match automatically another in surgical space. Generally, unconstrained least-squares is used for 3D rigid transform matrix, here we propose a constrained least-squares, constraint condition is the orthogonal matrix, iteration is used to make the matrix orthogonal, up to optimization matrix. Experiments show markers automatic matching algorithm is very quick and correct, constrained least-squares can increase the reliability and accuracy of the 3D rigid transform.