This article focuses on new virtual advances to solve technical problems usually encountered by paleontologists when using X-ray computed tomography (XCT), such as (i) the limited scanning envelope (i.e., field of view of CT systems/machines) to acquire data on large structures; (ii) the use in the same study of biological objects acquired with different types of computed tomography systems (medical and laboratory XCTs and laboratory high-resolution XμCT) and therefore different resolutions; and (iii) matrix removal within the fossil (e.g., cranial cavities, intratrabecular cavities, among other cavities). All these problems are very common in paleontology, and therefore, solving them is important to save effort and the time invested in data processing. In this article, we propose various solutions to tackle these issues, based on new technical advances focused on improving and processing the images obtained from XCT. Other aspects include image filtering and histogram calibration to remove background noise and artifacts. Such artifacts can result from dense mineral inclusion occurring during the fossilization process or derived from anthropogenic restoration of the sample. Accordingly, here, we provide a protocol to acquire data on samples with size that exceed the scanning envelope of the X-ray tomography machine, joining the parts with enough accuracy, and we propose the use of the interpolation “bicubic” method. Moreover, using this method, it is possible to use medical/laboratory XCT data together with XμCT data and therefore opening new ways to manipulate the acquired data within the image stack. Another advantage is the use of plugins for quantitative analysis, which require data with isometric voxels, such as the plugin BoneJ of the software ImageJ. We also deal with the problem of removing the exogenous material that usually fills the internal cavities of fossils by means of using filters based on edge detection by gradient. Applying this method, it is possible to segment the non-bony matrix parts more quickly and efficiently. All of this is exemplified using five fossil skulls belonging to the cave bear group (Ursus spelaeus sensu lato), an iconic fossil species from the Pleistocene of Eurasia.

本文关注于新的虚拟技术进展，以解决古生物学家在使用X射线计算机断层扫描（XCT）时通常遇到的技术问题，例如（i）有限的扫描范围（即CT系统/机器的视野）来获取数据在大型结构上；（ii）在同一研究中使用通过不同类型的计算机断层扫描系统（医学和实验室XCT和实验室高分辨率XμCT）获得的生物物体，因此使用不同的分辨率；（iii）去除化石中的基质（例如，颅腔，小梁内腔以及其他腔）。所有这些问题在古生物学中都很常见，因此解决这些问题对于节省工作量和在数据处理上花费的时间很重要。在本文中，我们提出了各种解决方案来解决这些问题，基于专注于改进和处理从XCT获得的图像的新技术进步。其他方面包括图像过滤和直方图校准，以消除背景噪声和伪影。这些伪影可能是由于在化石过程中发生的密集矿物夹杂物引起的，或者是由于人为修复造成的。因此，在这里，我们提供了一种协议，用于获取尺寸超过X射线断层扫描仪扫描包络的样本上的数据，以足够的精度连接零件，并建议使用插值“双三次”方法。此外，使用此方法，可以将医学/实验室XCT数据与XμCT数据一起使用，因此开辟了新的方式来处理图像堆栈中的采集数据。另一个优势是使用插件进行定量分析，该插件需要具有等距体素的数据，例如ImageJ软件的插件BoneJ。我们还通过使用基于梯度边缘检测的过滤器来处理去除通常填充化石内部空腔的外源材料的问题。应用此方法，可以更快速有效地分割非骨骼矩阵部分。所有这些都以属于洞熊组的五个化石头骨为例（可以更快，更有效地分割非骨骼矩阵部分。所有这些都以属于洞熊组的五个化石头骨为例（可以更快，更有效地分割非骨骼矩阵部分。所有这些都以属于洞熊组的五个化石头骨为例（熊熊 sensu lato），一种来自欧亚大陆更新世的标志性化石。