Human Remains Identification Using Micro-CT, Chemometric and AI Methods in Forensic Experimental Reconstruction of Dental Patterns after Concentrated Sulphuric Acid Significant Impact

MOLECULES(2022)

引用 7|浏览2
暂无评分
摘要
(1) Teeth, in humans, represent the most resilient tissues. However, exposure to concentrated acids might lead to their dissolving, thus making human identification difficult. Teeth often contain dental restorations from materials that are even more resilient to acid impact. This paper aims to introduce a novel method for the 3D reconstruction of dental patterns as a crucial step for the digital identification of dental records. (2) With a combination of modern methods, including micro-computed tomography, cone-beam computer tomography, and attenuated total reflection, in conjunction with Fourier transform infrared spectroscopy and artificial intelligence convolutional neural network algorithms, this paper presents a method for 3D-dental-pattern reconstruction, and human remains identification. Our research studies the morphology of teeth, bone, and dental materials (amalgam, composite, glass-ionomer cement) under different periods of exposure to 75% sulfuric acid. (3) Our results reveal a significant volume loss in bone, enamel, dentine, as well as glass-ionomer cement. The results also reveal a significant resistance by the composite and amalgam dental materials to the impact of sulfuric acid, thus serving as strong parts in the dental-pattern mosaic. This paper also probably introduces the first successful artificial intelligence application in automated-forensic-CBCT segmentation. (4) Interdisciplinary cooperation, utilizing the mentioned technologies, can solve the problem of human remains identification with a 3D reconstruction of dental patterns and their 2D projections over existing ante-mortem records.
更多
查看译文
关键词
dental pattern, forensic dentistry, forensic radiology, forensic chemistry, machine learning, identification, dissolution, sulfuric acid, dentition, teeth, acid degradation
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要