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FRACTAL MODELLING AND ANALYSIS OF FLOW-FIELD IMAGES

机译:流场图像的分形建模与分析

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We introduce stochastic models for flow fields with parameters that dictate the scale-dependent (self-similar) character of the field and control the balance between its rotational vs compressive behaviour. The development of our models is motivated by the availability of imaging modalities that measure flow vector fields (flow-sensitive MRI and Doppler ultrasound). To study such data, we formulate estimators of the model parameters, and use them to quantify the Hurst exponent and directional properties of synthetic and real-world flow fields (measured by means of phase-contrast MRI) in 3D.
机译:我们为流场引入随机模型,其中参数决定了场的比例依赖性(自相似)字符,并控制其旋转VS压缩行为之间的平衡。 我们的模型的开发是通过测量流量矢量字段(流动敏感MRI和多普勒超声)的成像方式的可用性的动机。 为研究此类数据,我们制定模型参数的估算器,并使用它们在3D中量化合成和实际流域(通过相位对比MRI测量)的膝关节和定向性质。

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