Computed tomography (CT) scans provide anthropologists with a resource to generate three-dimensional (3D) digital skeletal material to expand quantification methods and build more standardized reference collections. The ability to visualize and manipulate the bone and skin of the face simultaneously in a 3D digital environment introduces a new way for forensic facial approximation practitioners to access and study the face. Craniofacial relationships can be quantified with landmarks or with surface-processing software that can quantify the geometric properties of the entire 3D facial surface. This article describes tools for the generation of dense facial tissue depth maps (FTDMs) using deidentified head CT scans of modern Americans from the Cancer Imaging Archive public repository and the open-source program Meshlab. CT scans of 43 females and 63 males from the archive were segmented and converted to 3D skull and face models using Mimics and exported as stereolithography files. All subsequent processing steps were performed in Meshlab. Heads were transformed to a common orientation and coordinate system using the coordinates of nasion, left orbitale, and left and right porion. Dense FTDMs were generated on hollowed, cropped face shells using the Hausdorff sampling filter. Two new point clouds consisting of the 3D coordinates for both skull and face were colorized on an RGB (red-green-blue) scale from 0.0 (red) to 40.0-mm (blue) depth values and exported as polygon (PLY) file format models with tissue depth values saved in the "vertex quality" field. FTDMs were also split into 1.0-mm increments to facilitate viewing of common depths across all faces. In total, 112 FTDMs were generated for 106 individuals. Minimum depth values ranged from 1.2 mm to 3.4 mm, indicating a common range of starting depths for most faces regardless of weight, as well as common locations for these values over the nasal bones, lateral orbital margins, and forehead superior to the supraorbital border. Maximum depths were found in the buccal region and neck, excluding the nose. Individuals with multiple scans at visibly different weights presented the greatest differences within larger depth areas such as the cheeks and neck, with little to no difference in the thinnest areas. A few individuals with minimum tissue depths at the lateral orbital margins and thicker tissues over the nasal bones (>3.0 mm) suggested the potential influence of nasal bone morphology on tissue depths. This study produced visual quantitative representations of the face and skull for forensic facial approximation research and practice that can be further analyzed or interacted with using free software. The presented tools can be applied to preexisting CT scans, traditional or cone beam, adult or subadult individuals, with or without landmarks, and regardless of head orientation, for forensic applications as well as for studies of facial variation and facial growth. In contrast with other facial mapping studies, this method produced both skull and face points based on replicable geometric relationships, producing multiple data outputs that are easily readable with software that is openly accessible.

中文翻译：

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用于计算机断层扫描模型的密集面部组织深度映射的开源工具。

计算机断层扫描（CT）扫描为人类学家提供了生成三维（3D）数字骨骼材料的资源，以扩展量化方法并建立更标准化的参考馆藏。在3D数字环境中同时可视化和操纵脸部骨骼和皮肤的能力为法医面部近似医生提供了一种新方法来访问和研究脸部。可以使用界标或可以量化整个3D面部表面的几何特性的表面处理软件来量化颅面关系。本文介绍了使用来自癌症影像档案馆公共资源库和开放源代码程序Meshlab的现代美国人的不知名头部CT扫描生成密集面部组织深度图（FTDM）的工具。将来自档案库的43位女性和63位男性的CT扫描进行分割，并使用Mimics转换为3D头骨和面部模型，并作为立体光刻文件导出。所有后续处理步骤均在Meshlab中执行。使用鼻梁，左眼眶以及左右部分的坐标，将头部转换为通用的方向和坐标系。使用Hausdorff采样过滤器在中空的裁剪后的面部外壳上生成密集的FTDM。将两个新的点云（由头骨和面部的3D坐标组成）以RGB（红-绿-蓝）标度从0.0（红色）到40.0-mm（蓝色）深度值着色，并导出为多边形（PLY）文件格式组织深度值保存在“顶点质量”字段中的模型。FTDM也分为1.0毫米的增量，以便于查看所有面上的共同深度。总共为106个人生成了112个FTDM。最小深度值介于1.2毫米至3.4毫米之间，这表明无论重量如何，大多数面部的起始深度的通用范围，以及这些值在鼻骨，眶外侧缘和额上眶上边界上方的通用位置。在颊区域和颈部（鼻子除外）发现最大深度。以明显不同的权重进行多次扫描的人在较大的深度区域（如脸颊和颈部）表现出最大的差异，而在最薄的区域则几乎没有差异。一些在外侧眼缘的组织深度最小且鼻骨上的组织较厚（> 3.0 mm）的个体提示鼻骨形态对组织深度的潜在影响。这项研究为法医面部近似研究和实践提供了面部和颅骨的视觉定量表示，可以使用免费软件进行进一步分析或与之交互。所介绍的工具可用于法医应用以及面部变化和面部生长研究的现有CT扫描，传统或锥形束，成人或亚成人（具有或不具有界标，并且无论头部方向如何）。与其他面部映射研究相反，此方法基于可复制的几何关系生成了头骨和脸部点，从而生成了多个数据输出，这些数据可通过可公开访问的软件轻松读取。