Ultrasound Tongue Contour Extraction using Dilated Convolutional Neural Network

One application of medical ultrasound imaging is to visualize and characterize human tongue shape and motion to study healthy or impaired speech production. Due to the low-contrast characteristic and noisy nature of ultrasound images, it requires knowledge about the tongue structure and ultrasound data interpretation for users to recognize tongue gestures. Moreover, quantitative analysis of tongue motion needs the tongue contour to be extracted, tracked and visualized automatically. This paper presents two novel deep neural networks that benefit from the ability of global prediction of encoding-decoding fully convolutional networks and the capability of full-resolution extraction of dilated convolutions. Assessment studies over datasets from different ultrasound machines disclosed the outstanding performances of the proposed models in terms of accuracy and robustness.