A SHAPE-BASED FRAMEWORK TO SEGMENTATION OF TONGUE CONTOURS FROM MRI DATA

We propose a shape-based variational framework to curve evolution for the segmentation of tongue contours from MRI mid-sagittal images. In particular, we first build a PCA model on tongue contours of different articulations of a reference speaker, and use it as shape priors. The parameters of the curve representation are then manipulated to minimize an objective function. The designed energy integrates both global and local image information. The global term extracts roughly the object in the whole image domain; while the local term improves precision inside a small neighborhood around the contour. Promising results and comparisons with other approaches demonstrate the efficiency of our new model.