冷冻切片是一种常见且公认的组织学方法,由于其易于访问,速度,和成本效率。然而,骨冷冻切片的创建尤其困难。在这项研究中,开发了一种用于小梁骨的冷冻切片方案,该方案提供了相对便宜且要求不高的石蜡或树脂包埋切片的替代方案。切片可以用常见的组织学染色方法染色,同时保持足够的质量来回答各种科学问题。此外,这项研究引入了一个自动协议来分析这些部分,使用户能够快速访问各种不同的染色。因此,建立了用于骨小梁样本的组织化学分析的基于神经网络的自动图像分析协议,与其他自动方法以及关于散射的手动分析相比,质量,和可靠性。与手动方法相比,这种高度自动化的协议可以处理大量的图像数据,其结果没有显着差异。即使这种方法专门用于骨组织,它适用于各种不同的组织和科学问题。
Cryosectioning is known as a common and well-established histological method, due to its easy accessibility, speed, and cost efficiency. However, the creation of bone cryosections is especially difficult. In this study, a cryosectioning protocol for trabecular bone that offers a relatively cheap and undemanding alternative to paraffin or resin embedded sectioning was developed. Sections are stainable with common histological dying methods while maintaining sufficient quality to answer a variety of scientific questions. Furthermore, this study introduces an automated protocol for analysing such sections, enabling users to rapidly access a wide range of different stainings. Therefore, an automated \'QuPath\' neural network-based image analysis protocol for histochemical analysis of trabecular bone samples was established, and compared to other automated approaches as well as manual analysis regarding scattering, quality, and reliability. This highly automated protocol can handle enormous amounts of image data with no significant differences in its results when compared with a manual method. Even though this method was applied specifically for bone tissue, it works for a wide variety of different tissues and scientific questions.