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Published on: August 30, 2013
Fractal-feature distance analysis of radiographic image
Kuniahru Imai1, Mitsuru Ikeda, Yukihiro Enchi
1Department of Radiological Technology, Nagoya University School of Health Sciences, 1-20 Daikominami 1-chome, Higashi-ku, Nagoya 461-8673, Japan. imai@met.nagoya-u.ac.jp
Rationale And Objectives:
We have conducted a fractal analysis of low-dose digital chest phantom radiographs and evaluated the relationship between the fractal-feature distance and the tube current-exposure time product.
Materials And Methods:
Chest phantom radiographs were obtained at various mAs values (0.5-4.0 mAs) and 140 kVp with a computed radiography system, and the reference images were acquired at 13 mAs. The lung field images were converted to binary images after processing them using the rolling-ball technique; a fractal analysis was conducted using the box-counting method for these binary images. The fractal-feature distances between the low-dose and reference images were calculated using the fractal dimension and the complexity.
Results:
For all binary images of lung fields, the relationship between the length of the square boxes and the number of boxes needed to cover the positive pixels of the binary image was linear on a log-log scale (r > or = 0.99). For mAs > or = 3.0, the fractal-feature distances were almost constant, whereas for mAs < or = 2.5, they increased depending on the reduction in mAs values.
Conclusion:
We have shown that a binary image of the lung field obtained from a chest phantom radiograph can be analyzed by the box-counting method and that its fractal-feature distance grows as the radiation dose declines.
