Paper
13 October 1987 Fractal-Based Image Analysis In Radiological Applications
S. Dellepiane, S. B. Serpico, G. Vernazza, R. Viviani
Author Affiliations +
Proceedings Volume 0845, Visual Communications and Image Processing II; (1987) https://doi.org/10.1117/12.976530
Event: Cambridge Symposium on Optics in Medicine and Visual Image Processing, 1987, San Diego, CA, United States
Abstract
We present some preliminary results of a study aimed to assess the actual effectiveness of fractal theory and to define its limitations in the area of medical image analysis for texture description, in particular, in radiological applications. A general analysis to select appropriate parameters (mask size, tolerance on fractal dimension estimation, etc.) has been performed on synthetically generated images of known fractal dimensions. Moreover, we analyzed some radiological images of human organs in which pathological areas can be observed. Input images were subdivided into blocks of 6x6 pixels; then, for each block, the fractal dimension was computed in order to create fractal images whose intensity was related to the D value, i.e., texture behaviour. Results revealed that the fractal images could point out the differences between normal and pathological tissues. By applying histogram-splitting segmentation to the fractal images, pathological areas were isolated. Two different techniques (i.e., the method developed by Pentland and the "blanket" method) were employed to obtain fractal dimension values, and the results were compared; in both cases, the appropriateness of the fractal description of the original images was verified.
© (1987) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
S. Dellepiane, S. B. Serpico, G. Vernazza, and R. Viviani "Fractal-Based Image Analysis In Radiological Applications", Proc. SPIE 0845, Visual Communications and Image Processing II, (13 October 1987); https://doi.org/10.1117/12.976530
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Cited by 12 scholarly publications and 1 patent.
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KEYWORDS
Fractal analysis

Image segmentation

Image processing

Image analysis

Tissues

Visual communications

Lung

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