We created a method for three-dimensional registration of medical scanner image volumes to images of physical tissue sections or other volumes, and evaluated its accuracy. The method is applicable for many animal experiments, and we are applying it to evaluate interventional MRI imaging of thermal ablation and to quantify in vivo drug release from a new device for localized, controlled release. The method computes an optimum set of rigid body registration parameters by iterative minimization of the Euclidean distances between automatically generated correspondence points, along manually selected fiducial needle paths, and optional point landmarks. For numerically simulated registrations, using two needle paths over a range of needle orientations, median voxel displacement errors depended only on needle localization error when the angle between needles was at least 15 degrees. For parameters typical of our in vivo experiments, the median error was <EQ0.18 mm. In addition, we determined that the distance objective function was a useful diagnostic for predicting registration quality. To evaluate the registration quality of physical specimens, we computed the misregistration for a needle not considered during the optimization procedure. We registered an ex vivo sheep brain MR volume with another MR volume and tissue section photographs, using various combinations of needle and point landmarks. Registration error was always <EQ0.65 mm for MR-to-MR registrations and <EQ0.9 mm for MR to tissue section registrations. We conclude that our method provides sufficient spatial correspondence to facilitate comparison of 3D image data with data from gross pathology tissue sections and histology.