Region segmentation in the frequency domain applied to upper airway real-time magnetic resonance images.
We describe a method for unsupervised region segmentation of an image using its spatial frequency domain representation. The algorithm was designed to process large sequences of real-time magnetic resonance (MR) images containing the 2-D midsagittal view of a human vocal tract airway. The segmentation algorithm uses an anatomically informed object model, whose fit to the observed image data is hierarchically optimized using a gradient descent procedure. The goal of the algorithm is to automatically extract the time-varying vocal tract outline and the position of the articulators to facilitate the study of the shaping of the vocal tract during speech production.
Bresch
Erik
E
Department of Electrical Engineering, University of Southern California, Los Angeles, CA 90089, USA. bresch@usc.edu
Narayanan
Shrikanth
S
D000465:Algorithms; D005583:Fourier Analysis; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007830:Larynx / Q000033:anatomy & histology* / Q000502:physiology; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008954:Models, Biological; D009055:Mouth / Q000033:anatomy & histology* / Q000502:physiology; D019047:Phantoms, Imaging; D010614:Pharynx / Q000033:anatomy & histology* / Q000502:physiology; D013060:Speech / Q000502:physiology*; D014827:Vocal Cords / Q000502:physiology