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Proceedings Paper

Application Of Fractal Texture Analysis To Segmentation Of Dental Radiographs
Author(s): Walter S. Kuklinski; Kavitha Chandra; Urs E. Ruttirmann; Richard L. Webber
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Paper Abstract

This work discusses the development of an image segmentation algorithm that utilizes fractional Brownian motion as a fractal texture model. Additionally a second feature, the correlation coefficient of the regression analysis associated with the fractal dimension computation, is also used to assess which regions of the radiograph are well described by the fractional Brownian motion model and hence, are more likely to be bone. The resulting three dimension feature space consisting of the local fractal dimension, radiograph intensities and regression analysis correlation coefficient was partitioned to identify each pixel of the radiographs as being either bone, teeth, or a boundary between these entities. The results obtained in this study indicate the potential utility of a textural based algorithm for segmentation of dental radiographs.

Paper Details

Date Published: 25 May 1989
PDF: 7 pages
Proc. SPIE 1092, Medical Imaging III: Image Processing, (25 May 1989); doi: 10.1117/12.953251
Show Author Affiliations
Walter S. Kuklinski, University of Lowell (United States)
Kavitha Chandra, University of Lowell (United States)
Urs E. Ruttirmann, National Institutes of Health (United States)
Richard L. Webber, National Institutes of Health (United States)


Published in SPIE Proceedings Vol. 1092:
Medical Imaging III: Image Processing
Samuel J. Dwyer; R. Gilbert Jost; Roger H. Schneider, Editor(s)

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