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A Vocal Tract Segmentation from MR Images using Level Set Method
RAMOU Naim, CHETIH Nabil* and GUERTI Mhania**
Abstract This paper deals with the segmentation of Vocal tract from Magnetic resonance image which is the major interest for the diagnosis and monitoring of articulations disorders. Our challenge is the implementation of a method that takes ownership of local segmentation geodesic active contours and the property of the global segmentation of Chan and Vese model to automate the process of extracting vocal tract contour from MR images used for articulations and visual speech analysis. The objective of this work is to investigate the robustness of this model on different MRI phoneme. As a result of this study, we found that the proposed method is also effective and robust.
Keyword Level set segmentation, MRI segmentation, Articulations disorders
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