Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Human Remains Identification Using Micro-CT, Spectroscopic and A.I. Methods in Forensic Experimental Reconstruction of Dental Patterns After Concentrated Acid Significant Impact

Version 1 : Received: 4 January 2022 / Approved: 6 January 2022 / Online: 6 January 2022 (09:33:53 CET)

How to cite: Thurzo, A.; Jančovičová, V.; Hain, M.; Thurzo, M.; Novák, B.; Kosnáčová, H.; Lehotská, V.; Moravanský, N.; Varga, I. Human Remains Identification Using Micro-CT, Spectroscopic and A.I. Methods in Forensic Experimental Reconstruction of Dental Patterns After Concentrated Acid Significant Impact. Preprints 2022, 2022010049 (doi: 10.20944/preprints202201.0049.v1). Thurzo, A.; Jančovičová, V.; Hain, M.; Thurzo, M.; Novák, B.; Kosnáčová, H.; Lehotská, V.; Moravanský, N.; Varga, I. Human Remains Identification Using Micro-CT, Spectroscopic and A.I. Methods in Forensic Experimental Reconstruction of Dental Patterns After Concentrated Acid Significant Impact. Preprints 2022, 2022010049 (doi: 10.20944/preprints202201.0049.v1).

Abstract

(1) Human teeth are the most resilient tissues in the body. However, exposure to concentrated acids might lead to their obliteration, thus making human identification difficult. Teeth often contain dental restorations from materials that are even more resilient to acid impact. This paper introduces novel method of 3D reconstruction of dental patterns as a crucial step for digital identification with dental records.; (2) With combination of modern methods of Micro-Computed Tomography, Cone Beam Computed Tomography, Attenuated Total Reflection in conjunction with Fourier-Transform Infrared Spectroscopy and Artificial Intelligence Convolutional Neural Network algorithms, the paper presents the way of 3D dental pattern reconstruction and human remains identification. Research studies morphology of teeth, bone and dental materials (Amalgam, Composite, Glass-ionomer cement) under different periods of exposure to 75% sulfuric acid; (3) Results reveal significant volume loss in bone, enamel, dentine and as well glass-ionomer cement. Results also reveal significant resistance of composite and amalgam dental materials to sulfuric acid impact, thus serving as strong parts in the dental pattern mosaic. Paper also introduces probably first successful artificial intelligence application in automated forensic CBCT segmentation.; (4) Interdisciplinary cooperation utilizing mentioned technologies can solve problem of human remains identification with 3D reconstruction of dental patterns and their 2D projections over existing ante-mortem records.

Keywords

Dental Pattern; Forensic Anthropology; Forensic Odontology; Forensic Dentistry; Forensic Ra-diology; Forensic Chemistry; Forensic science; Machine Learning; Identification; Dental materials; Acid solution; Dissolution; Sulfuric acid; Dentition; Teeth; Acid degradation;

Subject

MEDICINE & PHARMACOLOGY, Dentistry

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