Registration based on B-spline transformations has attracted much attention in medical image processing recently. Non-rigid registration provides the basis for many important techniques, such as statistical shape modeling. Validating the results, however, remains difficult--especially in intersubject registration. This work explores the ability of B-spline registration methods to capture intersubject shape deformations. We study the effect of different established and new shape representations, similarity measures and optimization strategies on the matching quality. To this end we conduct experiments on synthetic shapes representing deformations which typically may arise in intersubject registration, as well as on real patient data of the liver and pelvic bone. The experiments clearly reveal the influence of each component on the registration performance. The results may serve as a guideline for assessing intensity based registration.