In Vivo 3-dimensional Wrist Kinematics: Using Volume-based Registration

INTRODUCTION: Registration is a fundamental task in image processing used to match two or more pictures taken, for example, at different times, from different sensors or from different viewpoints. Such procedures are frequently needed in medical applications not only within clinical diagnostic settings, but prominently so in the area of planning and evaluation of surgical and radiotherapeutical procedures. The bulk of registration algorithms in medical imaging can be classified as being either frame based, point based, surface based, or voxel based ([1],[2],[3]). In kinematics study, current approaches do mainly concentrate on surface based registration. Surface registration requires segmentation, which is delineation of corresponding surfaces in each of the images separately. A drawback of surface registration methods is that the registration accuracy is limited to the accuracy of the segmentation step. Volume-based registration methods stand apart from the other registration methods by the fact that they operate directly on the image grey values, without prior data reduction by the user or segmentation. Volume-based registration methods optimize a measuring of the similarity of all geometrically corresponding voxel pairs for some feature. The main advantage of volume-based registrat ion methods is that feature calculation is straightforward, such that the accuracy of these methods is not limited by segmentation errors as in surface based registration methods. The primay aim of this study is to evaluate in vivo 3-dimensional kinematics of the wrist joint during flexion-extension motion (FEM) and radio-ulna deviation (RUD). We noninvasively studied the radiocarpal and the midcarpal joints of 5 healthy volunteers using a volume-based registration algorithm. Secondly, we evaluated the accuracy of the volume-based registration of three dimensional magnetic resonance imaging (3-D MRI) using simulated MR images.