Classification of Porcine Cranial Fracture Patterns Using a Fracture Printing Interface

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• 作者：Feng Wei ; Serhat Selç ; uk Bucak ; Jennifer M. Vollner ; Todd W. Fenton ; Anil K. Jain and Roger C. Haut
• 刊名：Journal of Forensic Sciences
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：62
• 期：1
• 页码：30-38
• 全文大小：545K
• ISSN：1556-4029

文摘

Distinguishing between accidental and abusive head trauma in children can be difficult, as there is a lack of baseline data for pediatric cranial fracture patterns. A porcine head model has recently been developed and utilized in a series of studies to investigate the effects of impact energy level, surface type, and constraint condition on cranial fracture patterns. In the current study, an automated pattern recognition method, or a fracture printing interface (FPI), was developed to classify cranial fracture patterns that were associated with different impact scenarios documented in previous experiments. The FPI accurately predicted the energy level when the impact surface type was rigid. Additionally, the FPI was exceedingly successful in determining fractures caused by skulls being dropped with a high-level energy (97% accuracy). The FPI, currently developed on the porcine data, may in the future be transformed to the task of cranial fracture pattern classification for human infant skulls.