Background and Objective: the acquisition of microscopic images of human bones is a complex and expensive process. Moreover, the objective of obtaining a large data bank with microscopic images in order to carry out massive studies or to train automatic generation algorithms is not an option. Consequently, most of the current work focuses on the analysis of small regions captured by a microscope. The aim is the development of a tool to represent bone tissue at microscopic levels which is suitable for performing physical simulations, as well as for the diagnosis of various diseases. This work includes the whole process from the digitization of a human bone to the generation of bone tissue in a determined area of the bone selected through a cutting plane.

Methods: based on the anatomy of the bone structure, the parameters that allow the representation of the bone tissue at mesoscale level have been analyzed. Although the models are randomly generated, they are based on statistical parameters. The model generator is based on the analysis of images of bone tissue and its parameters, performing a representation of each of its relevant structures in a way that fulfils these parameters.

Results: the tool is useful for the virtual generation of bone tissue that satisfies the main characteristics of the cortical bone. The models obtained have been favorably evaluated in two stages. In the first stage, a scientific group has examined a set of images, in which images of the models generated were mixed with images obtained through traditional methods. Then, the physical characteristics of the generated tissue have been compared with the morphology of the bone tissue.

Conclusions: the model generator allows us to perform precise simulations in order to obtain realistic images with physical characteristics in accordance with reality. It is necessary to emphasize that even though the most relevant structures are included, the proposed model generator can be expanded to include new parameters or elements, so that it can be adapted to new needs. It could even break down randomness and parameterize it completely in order to allow the recreation of the tissue conditions of other studies.

背景与目的：人体骨骼显微图像的采集是一个复杂而昂贵的过程。此外，获得带有微观图像的大型数据库以进行大量研究或训练自动生成算法的目标不是一个选择。因此，当前的大部分工作都集中在分析显微镜捕获的小区域上。目的是开发一种在微观水平上代表骨骼组织的工具，该工具适用于执行物理模拟以及各种疾病的诊断。这项工作包括从人体骨骼的数字化到在通过切割平面选择的骨骼的确定区域中生成骨骼组织的整个过程。

方法：根据骨骼结构的解剖结构，分析了可以在中尺度水平上表示骨骼组织的参数。尽管模型是随机生成的，但它们是基于统计参数的。模型生成器基于对骨组织图像及其参数的分析，以满足这些参数的方式对每个相关结构进行表示。

结果：该工具可用于虚拟生成满足皮质骨主要特征的骨组织。获得的模型已在两个阶段得到了令人满意的评估。在第一阶段，一个科学小组检查了一组图像，其中将生成的模型的图像与通过传统方法获得的图像进行了混合。然后，将产生的组织的物理特性与骨组织的形态进行了比较。

结论：模型生成器允许我们执行精确的仿真，以便获得具有符合实际情况的物理特征的逼真的图像。需要强调的是，即使包括最相关的结构，建议的模型生成器也可以扩展为包括新的参数或元素，以便可以适应新的需求。它甚至可以分解随机性并将其完全参数化，以允许其他研究的组织状况得以恢复。