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死后计算机断层扫描数据可视化技术在法医死亡调查中的研究综述。

A review of visualization techniques of post-mortem computed tomography data for forensic death investigations.

机构信息

Zurich Institute of Forensic Medicine, University of Zurich, Zurich, Switzerland.

Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland.

出版信息

Int J Legal Med. 2021 Sep;135(5):1855-1867. doi: 10.1007/s00414-021-02581-4. Epub 2021 Apr 30.

DOI:10.1007/s00414-021-02581-4
PMID:33931808
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8354982/
Abstract

Postmortem computed tomography (PMCT) is a standard image modality used in forensic death investigations. Case- and audience-specific visualizations are vital for identifying relevant findings and communicating them appropriately. Different data types and visualization methods exist in 2D and 3D, and all of these types have specific applications. 2D visualizations are more suited for the radiological assessment of PMCT data because they allow the depiction of subtle details. 3D visualizations are better suited for creating visualizations for medical laypersons, such as state attorneys, because they maintain the anatomical context. Visualizations can be refined by using additional techniques, such as annotation or layering. Specialized methods such as 3D printing and virtual and augmented reality often require data conversion. The resulting data can also be used to combine PMCT data with other 3D data such as crime scene laser scans to create crime scene reconstructions. Knowledge of these techniques is essential for the successful handling of PMCT data in a forensic setting. In this review, we present an overview of current visualization techniques for PMCT.

摘要

死后计算机断层扫描(PMCT)是法医学死亡调查中使用的标准成像方式。针对具体案例和受众的可视化对于识别相关发现并进行适当的交流至关重要。二维和三维中存在不同的数据类型和可视化方法,所有这些类型都有特定的应用。二维可视化更适合 PMCT 数据的放射学评估,因为它们可以描绘细微的细节。三维可视化更适合为医学外行(如州检察官)创建可视化效果,因为它们保持了解剖结构的连贯性。通过使用注释或分层等附加技术,可以对可视化效果进行细化。特殊方法,如 3D 打印和虚拟与增强现实,通常需要进行数据转换。生成的数据还可以用于将 PMCT 数据与犯罪现场激光扫描等其他 3D 数据相结合,以创建犯罪现场重建。在法医环境中成功处理 PMCT 数据需要掌握这些技术。在这篇综述中,我们介绍了 PMCT 的当前可视化技术概述。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cac4/8354982/4e71cf3043b1/414_2021_2581_Fig12_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cac4/8354982/6168108b302d/414_2021_2581_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cac4/8354982/21f735e24c07/414_2021_2581_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cac4/8354982/bc3b5453dc2f/414_2021_2581_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cac4/8354982/601c1706c6c4/414_2021_2581_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cac4/8354982/e57fbd375734/414_2021_2581_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cac4/8354982/b035d18771de/414_2021_2581_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cac4/8354982/af4393241713/414_2021_2581_Fig9_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cac4/8354982/e6b0f64fa89b/414_2021_2581_Fig10_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cac4/8354982/99ccf1ba5157/414_2021_2581_Fig11_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cac4/8354982/4e71cf3043b1/414_2021_2581_Fig12_HTML.jpg

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