Imai K, Ikeda M, Enchi Y, Niimi T
Department of Radiological Technology, Nagoya University School of Health Sciences, Nagoya, Japan.
Australas Phys Eng Sci Med. 2009 Dec;32(4):188-95. doi: 10.1007/BF03179238.
The purposes of our studies are to examine whether or not fractal-feature distance deduced from virtual volume method can simulate observer performance indices and to investigate the physical meaning of pseudo fractal dimension and complexity. Contrast-detail (C-D) phantom radiographs were obtained at various mAs values (0.5 - 4.0 mAs) and 140 kVp with a computed radiography system, and the reference image was acquired at 13 mAs. For all C-D images, fractal analysis was conducted using the virtual volume method that was devised with a fractional Brownian motion model. The fractal-feature distances between the considered and reference images were calculated using pseudo fractal dimension and complexity. Further, we have performed the C-D analysis in which ten radiologists participated, and compared the fractal-feature distances with the image quality figures (IQF). To clarify the physical meaning of the pseudo fractal dimension and complexity, contrast-to-noise ratio (CNR) and standard deviation (SD) of images noise were calculated for each mAs and compared with the pseudo fractal dimension and complexity, respectively. A strong linear correlation was found between the fractal-feature distance and IQF. The pseudo fractal dimensions became large as CNR increased. Further, a linear correlation was found between the exponential complexity and image noise SD.
我们研究的目的是检验从虚拟体积法推导得出的分形特征距离是否能够模拟观察者性能指标，并探究伪分形维数和复杂度的物理意义。使用计算机X线摄影系统，在不同的毫安秒值（0.5 - 4.0毫安秒）和140千伏峰值电压下获取对比度-细节（C-D）体模X线片，参考图像在13毫安秒时采集。对于所有C-D图像，使用基于分数布朗运动模型设计的虚拟体积法进行分形分析。利用伪分形维数和复杂度计算考虑图像与参考图像之间的分形特征距离。此外，我们进行了有十名放射科医生参与的C-D分析，并将分形特征距离与图像质量指标（IQF）进行比较。为了阐明伪分形维数和复杂度的物理意义，计算了每个毫安秒值下图像的对比度噪声比（CNR）和图像噪声的标准差（SD），并分别与伪分形维数和复杂度进行比较。发现分形特征距离与IQF之间存在强线性相关性。随着CNR增加，伪分形维数变大。此外，发现指数复杂度与图像噪声SD之间存在线性相关性。
