Application and performance of artificial intelligence technology in forensic odontology – A systematic review

Khanagar, Sanjeev; Vishwanathaiah, Satish; Naik, Sachin; Al‐Kheraif, Abdulaziz A.; Divakar, Darshan Devang; Sarode, Sachin C.; Bhandi, Shilpa; Patil, Shankargouda

doi:10.1016/j.legalmed.2020.101826

Cited by 55 publications

(31 citation statements)

References 30 publications

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“…The use of automated techniques in forensic dentistry has been applied to several purposes including sex differentiation, age estimation, prediction of mandibular morphology, and identification of bite marks. 24 Matsuda et al (2020) reported the utility of using neural network methods to match a small sample of simulated AM and PM panoramic radiographs. The findings of this study are consistent with the accuracy levels reported by those authors, which ranged from 80% to 100%.…”

Section: Discussionmentioning

confidence: 99%

A pilot study of an automated personal identification process: Applying machine learning to panoramic radiographs

et al. 2021

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Purpose This study aimed to assess the usefulness of machine learning and automation techniques to match pairs of panoramic radiographs for personal identification. Materials and Methods Two hundred panoramic radiographs from 100 patients (50 males and 50 females) were randomly selected from a private radiological service database. Initially, 14 linear and angular measurements of the radiographs were made by an expert. Eight ratio indices derived from the original measurements were applied to a statistical algorithm to match radiographs from the same patients, simulating a semi-automated personal identification process. Subsequently, measurements were automatically generated using a deep neural network for image recognition, simulating a fully automated personal identification process. Results Approximately 85% of the radiographs were correctly matched by the automated personal identification process. In a limited number of cases, the image recognition algorithm identified 2 potential matches for the same individual. No statistically significant differences were found between measurements performed by the expert on panoramic radiographs from the same patients. Conclusion Personal identification might be performed with the aid of image recognition algorithms and machine learning techniques. This approach will likely facilitate the complex task of personal identification by performing an initial screening of radiographs and matching ante-mortem and post-mortem images from the same individuals.

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Section: Discussionmentioning

confidence: 99%

A pilot study of an automated personal identification process: Applying machine learning to panoramic radiographs

et al. 2021

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“…In field of forensic radiology, a specific algorithm can be created which further helps to identify distinct microscopic characteristics forming an array of specific features in the 3D space that would represent a new form of AI -identified dental patterns hardly comprehensible with a human brain. AI is advancing in the field of dental radiology and will bring a paradigm shift within the next decade [7,9,[35][36][37][38][39][40][41][42][43][44][45][46].…”

Section: The Technology Of Advanced Artificial Intelligencementioning

confidence: 99%

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

Thurzo¹,

Jančovičová²,

Hain³

et al. 2022

Preprint

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(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.

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“…Sin embargo, muchos de estos estudios se han realizado en modelos experimentales y constituyen una limitación importante. Dentro de los parámetros en los que aún no hay evidencia en IA recomendados por una reciente revisión sistemática tenemos las huellas labiales, rugas palatinas y la translucidez dentinaria 28 . Podría también recomendarse el uso de IA en la identificación racial por parte del análisis realizado en odontología forense.…”

Section: Revisión Y Discusiónunclassified

Aplicación de la inteligencia artificial en Odontología

Cacñahuaray-Martínez

Gómez-Meza

Lamas-Lara

et al. 2021

Odontol Sanmarquina

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En este artículo se revisó sobre inteligencia artificial (IA) y su aplicación en el campo odontológico. El objetivo fue revisar la evidencia sobre inteligencia artificial y su aplicación en las diferentes especialidades odontológicas. Se realizó una búsqueda en las bases de datos de Medline/PubMed, Scopus y Web of Science desde el año 2017 al 2021. Se encontraron 321 artículos, de los cuales se seleccionaron 62, que mostraron la aplicación de la IA en seis especialidades: periodoncia, implantología, odontología forense, medicina y patología oral, ortodoncia y diagnóstico/cariología/endodoncia. Se encontró que la especialidad con más artículos sobre el tópico de IA fue la de diagnóstico/cariología/endodoncia y el tipo de inteligencia artificial que más se utilizó fue el de red neural convolucional. Se concluyó que la IA se está utilizando ampliamente en odontología demostrando resultados prometedores ya que muestran una precisión equivalente a la de diferentes especialistas capacitados y en algunos casos superan los errores humanos demostrando excelentes resultados.

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Application and performance of artificial intelligence technology in forensic odontology – A systematic review

Cited by 55 publications

References 30 publications

A pilot study of an automated personal identification process: Applying machine learning to panoramic radiographs

A pilot study of an automated personal identification process: Applying machine learning to panoramic radiographs

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

Aplicación de la inteligencia artificial en Odontología

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