Evaluating partial surface matching for fracture reduction assessment

We present a method for evaluating the quality of acetabular fracture reductions in computer-assisted orthopaedic surgery (CAOS), which is analogous to evaluating the accuracy reached by a partial surface matching algorithm. We formulate the problem as a two-step procedure: (1) Characterizing the fracture surfaces and (2) providing a useful quantitative value to assess a fracture reduction procedure or a partial surface matching algorithm. To characterize 3D models of the fracture surfaces, we use clustering in conjunction with two similarity measures that we introduce in this paper. The similarity measures take into account features such as orientation and size of the triangles, as well as connectivity information. Our method for obtaining a quantitative value enables for the approximation of the interstitial volume left between bone fragments resulting from a fracture, and thus allows for the evaluation of the accuracy of the fragments' repositioning.