The objective of this work was to develop a computational approach for quantifying the three-dimensional (3D) thickness distribution of articular cartilage with magnetic resonance (MR) imaging, independent of the imaging plane, and to test the reproducibility of the method in the living. An algorithm was implemented, based on a 3D Euclidean distance transformation, and its accuracy was assessed in geometric test objects, for which an analytic solution was available. The precision of the method was evaluated in six replicated MR data sets of the knee joint cartilage of eight volunteers. The algorithm produced 3D thickness values identical to those of the analytic solutions in the test objects. The reproducibility of the mean cartilage thickness in the patellar and tibial cartilages was 1.5-3.4% (root-mean-square average of the individual coefficient of variation percent), that of the maximal thickness 2.1-7.9%, and that of the thickness distribution 2.3-6.1%. The method presented allows for noninvasive analysis of 3D cartilage thickness from MR images in biomechanical and clinical investigations.