Vargas Isaac, Alhallak Kinan, Kolenc Olivia I, Jenkins Samir V, Griffin Robert J, Dings Ruud P M, Rajaram Narasimhan, Quinn Kyle P
Department of Biomedical Engineering, University of Arkansas, Fayetteville, AR 72701, USA.
Division of Radiation Biology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA.
Biomed Opt Express. 2018 Oct 9;9(11):5269-5279. doi: 10.1364/BOE.9.005269. eCollection 2018 Nov 1.
An improved technique for fractal characterization called the modified blanket method is introduced that can quantify surrounding fractal structures on a pixel by pixel basis without artifacts associated with scale-dependent image features such as object size. The method interprets images as topographical maps, obtaining information regarding the local surface area as a function of image resolution. Local fractal dimension (FD) can be quantified from the power law exponent derived from the surface area and image resolution relationship. We apply this technique on simulated cell images of known FD and compared the obtained values to power spectral density (PSD) analysis. Our method is sensitive to a wider FD range (2.0-4.5), having a mean error of 1.4% compared to 6% for PSD analysis. This increased sensitivity and an ability to compute regional FD properties enabled the discrimination of the differences in radiation resistant cancer cell responses that could not be detected using PSD analysis.
本文介绍了一种改进的分形特征描述技术——改进毯式方法，该方法可以逐像素量化周围的分形结构，而不会产生与诸如物体大小等尺度相关图像特征相关的伪影。该方法将图像解释为地形图，获取关于局部表面积与图像分辨率函数关系的信息。局部分形维数（FD）可以从由表面积和图像分辨率关系导出的幂律指数中量化。我们将此技术应用于已知FD的模拟细胞图像，并将获得的值与功率谱密度（PSD）分析进行比较。我们的方法对更宽的FD范围（2.0 - 4.5）敏感，平均误差为1.4%，而PSD分析的平均误差为6%。这种更高的灵敏度以及计算区域FD特性的能力使得能够区分使用PSD分析无法检测到的抗辐射癌细胞反应差异。
