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Article

Use of Advanced Artificial Intelligence in Forensic Medicine, Forensic Anthropology and Clinical Anatomy

by
Andrej Thurzo
1,2,3,*,
Helena Svobodová Kosnáčová
2,4,
Veronika Kurilová
5,
Silvester Kosmeľ
6,
Radoslav Beňuš
3,7,
Norbert Moravanský
3,8,
Peter Kováč
3,9,
Kristína Mikuš Kuracinová
10,
Michal Palkovič
10,11 and
Ivan Varga
12
1
Department of Stomatology and Maxillofacial Surgery, Faculty of Medicine, Comenius University in Bratislava, 81250 Bratislava, Slovakia
2
Department of Simulation and Virtual Medical Education, Faculty of Medicine, Comenius University, Sasinkova 4, 81272 Bratislava, Slovakia
3
forensic.sk Institute of Forensic Medical Analyses Ltd., Boženy Němcovej 8, 81104 Bratislava, Slovakia
4
Department of Genetics, Cancer Research Institute, Biomedical Research Center, Slovak Academy Sciences, Dúbravská Cesta 9, 84505 Bratislava, Slovakia
5
Faculty of Electrical Engineering and Information Technology, Slovak University of Technology, Ilkovičova 3, 81219 Bratislava, Slovakia
6
Deep Learning Engineering Department at Cognexa, Faculty of Informatics and Information Technologies, Slovak University of Technology, Ilkovičova 2, 84216 Bratislava, Slovakia
7
Department of Anthropology, Faculty of Natural Sciences, Comenius University in Bratislava, Mlynská dolina Ilkovičova 6, 84215 Bratislava, Slovakia
8
Institute of Forensic Medicine, Faculty of Medicine, Comenius University in Bratislava, Sasinkova 4, 81108 Bratislava, Slovakia
9
Department of Criminal Law and Criminology, Faculty of Law Trnava University, Kollárova 10, 91701 Trnava, Slovakia
10
Institute of Pathological Anatomy, Faculty of Medicine, Comenius University in Bratislava, Sasinkova 4, 81108 Bratislava, Slovakia
11
Forensic Medicine and Pathological Anatomy Department, Health Care Surveillance Authority (HCSA), Sasinkova 4, 81108 Bratislava, Slovakia
12
Institute of Histology and Embryology, Faculty of Medicine, Comenius University in Bratislava, 81372 Bratislava, Slovakia
 
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*
Author to whom correspondence should be addressed.
Healthcare 2021, 9(11), 1545; https://doi.org/10.3390/healthcare9111545
Submission received: 1 November 2021 / Revised: 10 November 2021 / Accepted: 10 November 2021 / Published: 12 November 2021
(This article belongs to the Special Issue New Trends in Forensic and Legal Medicine)
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Abstract

Three-dimensional convolutional neural networks (3D CNN) of artificial intelligence (AI) are potent in image processing and recognition using deep learning to perform generative and descriptive tasks. Compared to its predecessor, the advantage of CNN is that it automatically detects the important features without any human supervision. 3D CNN is used to extract features in three dimensions where input is a 3D volume or a sequence of 2D pictures, e.g., slices in a cone-beam computer tomography scan (CBCT). The main aim was to bridge interdisciplinary cooperation between forensic medical experts and deep learning engineers, emphasizing activating clinical forensic experts in the field with possibly basic knowledge of advanced artificial intelligence techniques with interest in its implementation in their efforts to advance forensic research further. This paper introduces a novel workflow of 3D CNN analysis of full-head CBCT scans. Authors explore the current and design customized 3D CNN application methods for particular forensic research in five perspectives: (1) sex determination, (2) biological age estimation, (3) 3D cephalometric landmark annotation, (4) growth vectors prediction, (5) facial soft-tissue estimation from the skull and vice versa. In conclusion, 3D CNN application can be a watershed moment in forensic medicine, leading to unprecedented improvement of forensic analysis workflows based on 3D neural networks.
Keywords: forensic medicine; forensic dentistry; forensic anthropology; 3D CNN; AI; deep learning; biological age determination; sex determination; 3D cephalometric; AI face estimation; growth prediction forensic medicine; forensic dentistry; forensic anthropology; 3D CNN; AI; deep learning; biological age determination; sex determination; 3D cephalometric; AI face estimation; growth prediction
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MDPI and ACS Style

Thurzo, A.; Kosnáčová, H.S.; Kurilová, V.; Kosmeľ, S.; Beňuš, R.; Moravanský, N.; Kováč, P.; Kuracinová, K.M.; Palkovič, M.; Varga, I. Use of Advanced Artificial Intelligence in Forensic Medicine, Forensic Anthropology and Clinical Anatomy. Healthcare 2021, 9, 1545. https://doi.org/10.3390/healthcare9111545

AMA Style

Thurzo A, Kosnáčová HS, Kurilová V, Kosmeľ S, Beňuš R, Moravanský N, Kováč P, Kuracinová KM, Palkovič M, Varga I. Use of Advanced Artificial Intelligence in Forensic Medicine, Forensic Anthropology and Clinical Anatomy. Healthcare. 2021; 9(11):1545. https://doi.org/10.3390/healthcare9111545

Chicago/Turabian Style

Thurzo, Andrej, Helena Svobodová Kosnáčová, Veronika Kurilová, Silvester Kosmeľ, Radoslav Beňuš, Norbert Moravanský, Peter Kováč, Kristína Mikuš Kuracinová, Michal Palkovič, and Ivan Varga. 2021. "Use of Advanced Artificial Intelligence in Forensic Medicine, Forensic Anthropology and Clinical Anatomy" Healthcare 9, no. 11: 1545. https://doi.org/10.3390/healthcare9111545

APA Style

Thurzo, A., Kosnáčová, H. S., Kurilová, V., Kosmeľ, S., Beňuš, R., Moravanský, N., Kováč, P., Kuracinová, K. M., Palkovič, M., & Varga, I. (2021). Use of Advanced Artificial Intelligence in Forensic Medicine, Forensic Anthropology and Clinical Anatomy. Healthcare, 9(11), 1545. https://doi.org/10.3390/healthcare9111545

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