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Proceedings Paper

Model-based segmentation of the tongue surface using a modified scale space filter
Author(s): Juergen Kelch; Berthold B. Wein
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Paper Abstract

Ultrasonic imaging is used in order to detect disturbed tongue movements during swallowing and articulation. On these real-time B-mode sonographic images, which represent a median sagittal plane through the tongue and the floor of the mouth, the physician normally marks the tongue surface (dorsum) manually to stress the shape information. Our work presents a solution to extract the tongue dorsum automatically. We use a modified scale space filter for basic segmentation. This edge detector is based on coarse-to-fine tracking by varying the smoothing parameter of the Laplacian-of-Gaussian filter (LoG). In this way contour segments of the tongue dorsum and other objects are extracted. A model of the tongue supports identification of the tongue segments and interpolation of the surface in the spatiotemporal space. Some segments include two or more objects -- like liquid and tongue. This is the reason why we form the tongue as a chain of elliptical structure elements. This model stresses a direction to detect the orientation of the tongue and is flexible enough to form any shape. These structure elements are matched to the scale space segments by correlation. A trainable cost path classifier selects the topological connections of the structure elements, which are linked by a spline interpolation. Finally virtual three-dimensional views of the contour surface in the spatiotemporal space are generated with different azimuthal angles for visualization.

Paper Details

Date Published: 22 October 1993
PDF: 7 pages
Proc. SPIE 2094, Visual Communications and Image Processing '93, (22 October 1993); doi: 10.1117/12.157945
Show Author Affiliations
Juergen Kelch, Reinische-Westfaelische Technische Hochschule Aachen (Germany)
Berthold B. Wein, Reinische-Westfaelische Technische Hochschule Aachen (Germany)


Published in SPIE Proceedings Vol. 2094:
Visual Communications and Image Processing '93
Barry G. Haskell; Hsueh-Ming Hang, Editor(s)

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