Automatic contour tracking in ultrasound images.

In this paper, a new automatic contour tracking system, EdgeTrak, for the ultrasound image sequences of human tongue is presented. The images are produced by a head and transducer support system (HATS). The noise and unrelated high-contrast edges in ultrasound images make it very difficult to automatically detect the correct tongue surfaces. In our tracking system, a novel active contour model is developed. Unlike the classical active contour models which only use gradient of the image as the image force, the proposed model incorporates the edge gradient and intensity information in local regions around each snake element. Different from other active contour models that use homogeneity of intensity in a region as the constraint and thus are only applied to closed contours, the proposed model applies local region information to open contours and can be used to track partial tongue surfaces in ultrasound images. The contour orientation is also taken into account so that any unnecessary edges in ultrasound images will be discarded. Dynamic programming is used as the optimisation method in our implementation. The proposed active contour model has been applied to human tongue tracking and its robustness and accuracy have been verified by quantitative comparison analysis to the tracking by speech scientists.