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

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 fe...

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Autores principales:	Andrej Thurzo, Helena Svobodová Kosnáčová, Veronika Kurilová, Silvester Kosmeľ, Radoslav Beňuš, Norbert Moravanský, Peter Kováč, Kristína Mikuš Kuracinová, Michal Palkovič, Ivan Varga
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	forensic medicine forensic dentistry forensic anthropology 3D CNN AI deep learning Medicine R
Acceso en línea:	https://doaj.org/article/d69c6f7f6c6649efaf105ed423b793e0
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id	oai:doaj.org-article:d69c6f7f6c6649efaf105ed423b793e0
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spelling	oai:doaj.org-article:d69c6f7f6c6649efaf105ed423b793e02021-11-25T17:45:58ZUse of Advanced Artificial Intelligence in Forensic Medicine, Forensic Anthropology and Clinical Anatomy10.3390/healthcare91115452227-9032https://doaj.org/article/d69c6f7f6c6649efaf105ed423b793e02021-11-01T00:00:00Zhttps://www.mdpi.com/2227-9032/9/11/1545https://doaj.org/toc/2227-9032Three-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.Andrej ThurzoHelena Svobodová KosnáčováVeronika KurilováSilvester KosmeľRadoslav BeňušNorbert MoravanskýPeter KováčKristína Mikuš KuracinováMichal PalkovičIvan VargaMDPI AGarticleforensic medicineforensic dentistryforensic anthropology3D CNNAIdeep learningMedicineRENHealthcare, Vol 9, Iss 1545, p 1545 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	forensic medicine forensic dentistry forensic anthropology 3D CNN AI deep learning Medicine R
spellingShingle	forensic medicine forensic dentistry forensic anthropology 3D CNN AI deep learning Medicine R Andrej Thurzo Helena Svobodová Kosnáčová Veronika Kurilová Silvester Kosmeľ Radoslav Beňuš Norbert Moravanský Peter Kováč Kristína Mikuš Kuracinová Michal Palkovič Ivan Varga Use of Advanced Artificial Intelligence in Forensic Medicine, Forensic Anthropology and Clinical Anatomy
description	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.
format	article
author	Andrej Thurzo Helena Svobodová Kosnáčová Veronika Kurilová Silvester Kosmeľ Radoslav Beňuš Norbert Moravanský Peter Kováč Kristína Mikuš Kuracinová Michal Palkovič Ivan Varga
author_facet	Andrej Thurzo Helena Svobodová Kosnáčová Veronika Kurilová Silvester Kosmeľ Radoslav Beňuš Norbert Moravanský Peter Kováč Kristína Mikuš Kuracinová Michal Palkovič Ivan Varga
author_sort	Andrej Thurzo
title	Use of Advanced Artificial Intelligence in Forensic Medicine, Forensic Anthropology and Clinical Anatomy
title_short	Use of Advanced Artificial Intelligence in Forensic Medicine, Forensic Anthropology and Clinical Anatomy
title_full	Use of Advanced Artificial Intelligence in Forensic Medicine, Forensic Anthropology and Clinical Anatomy
title_fullStr	Use of Advanced Artificial Intelligence in Forensic Medicine, Forensic Anthropology and Clinical Anatomy
title_full_unstemmed	Use of Advanced Artificial Intelligence in Forensic Medicine, Forensic Anthropology and Clinical Anatomy
title_sort	use of advanced artificial intelligence in forensic medicine, forensic anthropology and clinical anatomy
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/d69c6f7f6c6649efaf105ed423b793e0
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Use of Advanced Artificial Intelligence in Forensic Medicine, Forensic Anthropology and Clinical Anatomy

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