FRACTAL SPATIAL DISTRIBUTIONS OF INTRAORGAN FLOWS

之前已经发现了两种不同的分形描述 足以描述区域内流动的异质性 心和肺超过200倍的体素大小范围；其中一个是基于 统计上的自相似，另一个就是自相似的分支 算法。这两种方法给出了异质性的预测 心脏中的100微克水平相差两倍， 但两者都与可用的数据兼容，而现有数据并不兼容 足够准确。这个项目的目标是开发 分析提供数据的实验的方法 三个数量级的差距从之前的数据到 预测，并通过两种方式解决差距：第一， 开发新的方法来描述覆盖血管网络的 所有可观测数据(大约五到六个数量级) 其次，将这些分形图发展为工作假设 适用于整个范围的数据的方法。

Two different fractal descriptions have been previously found adequate to describe the heterogeneity of regional flows within the heart and lung over a 200-fold range of voxel sizes; one was based on statistical self similarity, the other on a self-similar branching algorithm. The two methods gave predictions of the heterogeneity at the 100 microgram level in the heart that differed by a factor of two, but were both compatible with the available data, which is not sufficiently accurate. The goals of this project are to develop methods for analyzing experiments providing data covering the three-order of magnitude gap from the previous data to the level of prediction, and to resolve the disparity in two ways: firstly, to develop new methods of describing the vascular network that cover the whole range of observable data (about five to six orders of magnitude) and secondly, to develop as working hypotheses those fractal approaches that do fit the data over the whole range.