In this paper, we localize the shape-determinative slices of the masseter, which plays a critical role in the mastication system, from magnetic resonance (MR) data sets for clinical purposes. Shape-based criteria were used to locate the candidates for determinative slices from training data. The localization process involves tracking of the centroid and detecting the locations where the structure of the masseter undergoes an abrupt change in orientation. Having determined all the candidates which satisfy the criteria, fuzzy-c-means (FCM) clustering technique was used to establish the determinative slices. Localization of these slices will facilitate the building of more accurate models. It will also allow for more accurate computerized extraction of the masseter from MR data. In our work here, a hybrid method to shape-based interpolation is used to build the masseter model from magnetic resonance (MR) data sets, and the mean overlap index (K) achieved is 87.7%. Extraction of the masseter was carried out using our earlier proposed method and the mean K achieved is 88.9%. This indicates good agreement between the results obtained using computerized technique and those contained using manual contour tracing.