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用于计算机断层扫描模型密集面部组织深度映射的开源工具

Open-Source Tools for Dense Facial Tissue Depth Mapping of Computed Tomography Models.

作者信息

Simmons-Ehrhardt Terrie, Falsetti Catyana, Falsetti Anthony B, Ehrhardt Christopher J

机构信息

1 School of World Studies, Virginia Commonwealth University, Richmond, Virginia, USA.

2 School of Geological Sciences and Urban Planning, Arizona State University, Tempe, Arizona, USA.

出版信息

Hum Biol. 2018 Jan;90(1):63-76.

PMID:30387384
Abstract

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.

摘要

计算机断层扫描(CT)为人类学家提供了一种资源,可生成三维(3D)数字骨骼材料,以扩展量化方法并建立更标准化的参考数据集。在3D数字环境中同时可视化和操作面部骨骼与皮肤的能力,为法医面部复原从业者提供了一种获取和研究面部的新方法。颅面关系可以通过地标进行量化,也可以使用能够量化整个3D面部表面几何特性的表面处理软件进行量化。本文介绍了利用癌症影像存档公共数据库中身份不明的现代美国人头部CT扫描数据以及开源程序MeshLab生成密集面部组织深度图(FTDM)的工具。从该数据库中选取了43名女性和63名男性的CT扫描数据,使用Mimics进行分割并转换为3D头骨和面部模型,然后导出为立体光刻文件。所有后续处理步骤均在MeshLab中进行。利用鼻根点、左眶下点以及左右耳点的坐标,将头部转换到一个共同的方向和坐标系。使用豪斯多夫采样滤波器在镂空、裁剪后的面部外壳上生成密集的FTDM。由头骨和面部的3D坐标组成的两个新点云,按照从0.0(红色)到40.0毫米(蓝色)的深度值在RGB(红-绿-蓝)尺度上进行着色,并导出为多边形(PLY)文件格式的模型,组织深度值保存在“顶点质量”字段中。FTDM还被分割为1.0毫米的增量,以便于查看所有面部的共同深度。总共为106名个体生成了112个FTDM。最小深度值范围为1.2毫米至3.4毫米,表明大多数面部的起始深度范围较为常见,与体重无关,且这些值在鼻骨、眶外侧缘以及眶上缘上方的前额处的位置也较为常见。最大深度出现在颊部区域和颈部,不包括鼻子。在体重明显不同时进行多次扫描的个体,在脸颊和颈部等较大深度区域差异最大,而在最薄区域几乎没有差异。少数个体在眶外侧缘的组织深度最小,鼻骨上方的组织较厚(>3.0毫米),这表明鼻骨形态可能对组织深度有影响。本研究为法医面部复原研究和实践生成了面部和头骨的视觉定量表示,可使用免费软件进一步分析或交互。所介绍的工具可应用于现有的CT扫描数据,包括传统CT或锥形束CT,适用于成人或亚成人个体,无论有无地标,且与头部方向无关,可用于法医应用以及面部变异和面部生长的研究。与其他面部映射研究相比,该方法基于可复制的几何关系生成了头骨和面部点,产生了多个易于用公开可用软件读取的数据输出。

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