PDF(Pubmed)
Abstract：
In forensic medicine, estimating human skeletal remains\' post-mortem interval (PMI) can be challenging. Following death, bones undergo a series of chemical and physical transformations due to their interactions with the surrounding environment. Post-mortem changes have been assessed using various methods, but estimating the PMI of skeletal remains could still be improved. We propose a new methodology with handheld hyperspectral imaging (HSI) system based on the first results from 104 human skeletal remains with PMIs ranging between 1 day and 2000 years. To differentiate between forensic and archaeological bone material, the Convolutional Neural Network analyzed 65.000 distinct diagnostic spectra: the classification accuracy was 0.58, 0.62, 0.73, 0.81, and 0.98 for PMIs of 0 week-2 weeks, 2 weeks-6 months, 6 months-1 year, 1 year-10 years, and >100 years, respectively. In conclusion, HSI can be used in forensic medicine to distinguish bone materials >100 years old from those <10 years old with an accuracy of 98%. The model has adequate predictive performance, and handheld HSI could serve as a novel approach to objectively and accurately determine the PMI of human skeletal remains.
摘要：
在法医学中，估计人类骨骼遗骸的死后间隔(PMI)可能是具有挑战性的。在死亡之后,骨骼由于与周围环境的相互作用而经历一系列化学和物理转化。验尸后的变化已使用各种方法进行评估，但是估计骨骼残骸的PMI仍然可以改进。我们提出了一种带有手持式高光谱成像（HSI）系统的新方法，该方法基于104个人体骨骼遗骸的首批结果，其PMI范围为1天至2000年。为了区分法医和考古骨骼材料，卷积神经网络分析了65.000个不同的诊断光谱：对于0周-2周的PMI，分类精度为0.58、0.62、0.73、0.81和0.98，2周-6个月,6个月-1年,1年-10年,超过100年,分别。总之,HSI可用于法医学以98%的准确度区分>100岁和<10岁的骨材料。该模型具有足够的预测性能，和手持式HSI可以作为一种客观准确地确定人类骨骼遗骸PMI的新方法。
