A Reliable Procedure for the Construction of a Statistical Shape Model of the Cranial Vault

Abstract

The application of CAx tools in surgery is representing a breakthrough for clinical practice, both in terms of effectiveness and costs. Working directly on the patient’s own diagnostic images, this approach provides powerful tools for pre-operative simulation, complex-surgery planning, quantitative evaluation of asymmetry or dysmorphism and for the design of the patient-specific instrumentation. To exploit its full potential, methodologies are being developed to automatize and simplify the existing tools and strategies, in order to make them available also to less experienced CAx users, or directly to the surgeons. With this aim, it is proposed a methodological procedure to automatically create a Statistical Shape Model of the cranial vault starting from a Training Set of pathologically unaffected adult crania. The Statistical Shape Model is useful as a template for a data-driven restoration of the physiological shape of the considered anatomy. The proposed procedure provides a reliable strategy for robust automatic detection of shape correspondence. Not requiring any user intervention, the number of samples in the Training Set can be increased at will to consequently increase the variability, and therefore the accuracy, of the resulting parametric model.