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Proceedings Paper

Adaptive textural segmentation of medical images
Author(s): Walter S. Kuklinski; Gordon S. Frost; Thomas MacLaughlin
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Paper Abstract

A number of important problems in medical imaging can be described as segmentation problems. Previous fractal-based image segmentation algorithms have used either the local fractal dimension alone or the local fractal dimension and the corresponding image intensity as features for subsequent pattern recognition algorithms. An image segmentation algorithm that utilized the local fractal dimension, image intensity, and the correlation coefficient of the local fractal dimension regression analysis computation, to produce a three-dimension feature space that was partitioned to identify specific pixels of dental radiographs as being either bone, teeth, or a boundary between bone and teeth also has been reported. In this work we formulated the segmentation process as a configurational optimization problem and discuss the application of simulated annealing optimization methods to the solution of this specific optimization problem. The configurational optimization method allows information about both, the degree of correspondence between a candidate segment and an assumed textural model, and morphological information about the candidate segment to be used in the segmentation process. To apply this configurational optimization technique with a fractal textural model however, requires the estimation of the fractal dimension of an irregularly shaped candidate segment. The potential utility of a discrete Gerchberg-Papoulis bandlimited extrapolation algorithm to the estimation of the fractal dimension of an irregularly shaped candidate segment is also discussed.

Paper Details

Date Published: 1 June 1992
PDF: 7 pages
Proc. SPIE 1652, Medical Imaging VI: Image Processing, (1 June 1992); doi: 10.1117/12.59409
Show Author Affiliations
Walter S. Kuklinski, Univ. of Massachusetts/Lowell (United States)
Gordon S. Frost, Univ. of Massachusetts/Lowell (United States)
Thomas MacLaughlin, Univ. of Massachusetts/Lowell (United States)


Published in SPIE Proceedings Vol. 1652:
Medical Imaging VI: Image Processing
Murray H. Loew, Editor(s)

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