Automatic landmarking as a convenient prerequisite for geometric morphometrics. Validation on cone beam computed tomography (CBCT)- based shape analysis of the nasal complex

Research output: Contribution to journalJournal articleResearchpeer-review

Standard

Automatic landmarking as a convenient prerequisite for geometric morphometrics. Validation on cone beam computed tomography (CBCT)- based shape analysis of the nasal complex. / Ridel, A F; Demeter, F; Galland, M; L'abbé, E N; Vandermeulen, D; Oettlé, A C.

In: Forensic Science International, Vol. 306, 110095, 2020.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Ridel, AF, Demeter, F, Galland, M, L'abbé, EN, Vandermeulen, D & Oettlé, AC 2020, 'Automatic landmarking as a convenient prerequisite for geometric morphometrics. Validation on cone beam computed tomography (CBCT)- based shape analysis of the nasal complex', Forensic Science International, vol. 306, 110095. https://doi.org/10.1016/j.forsciint.2019.110095

APA

Ridel, A. F., Demeter, F., Galland, M., L'abbé, E. N., Vandermeulen, D., & Oettlé, A. C. (2020). Automatic landmarking as a convenient prerequisite for geometric morphometrics. Validation on cone beam computed tomography (CBCT)- based shape analysis of the nasal complex. Forensic Science International, 306, [110095]. https://doi.org/10.1016/j.forsciint.2019.110095

Vancouver

Ridel AF, Demeter F, Galland M, L'abbé EN, Vandermeulen D, Oettlé AC. Automatic landmarking as a convenient prerequisite for geometric morphometrics. Validation on cone beam computed tomography (CBCT)- based shape analysis of the nasal complex. Forensic Science International. 2020;306. 110095. https://doi.org/10.1016/j.forsciint.2019.110095

Author

Ridel, A F ; Demeter, F ; Galland, M ; L'abbé, E N ; Vandermeulen, D ; Oettlé, A C. / Automatic landmarking as a convenient prerequisite for geometric morphometrics. Validation on cone beam computed tomography (CBCT)- based shape analysis of the nasal complex. In: Forensic Science International. 2020 ; Vol. 306.

Bibtex

@article{5c0102e578f740f69bfa965e5335b780,
title = "Automatic landmarking as a convenient prerequisite for geometric morphometrics. Validation on cone beam computed tomography (CBCT)- based shape analysis of the nasal complex",
abstract = "Manual landmarking is used in several manual and semi-automated prediction guidelines for approximation of the nose. The manual placement of landmarks may, however, render the analysis less repeatable due to observer subjectivity and, consequently, have an impact on the accuracy of the human facial approximation. In order to address this subjectivity and thereby improve facial approximations, we are developing an automated three-dimensional (3D) method based on an automatic dense landmarking procedure using non-rigid surface registration. The aim of this study was to validate the automatic landmarking method by comparing the intra-observer errors (INTRA-OE) and inter-observer errors (INTER-OE) between automatic and manual landmarking. Cone beam computed tomography (CBCT) scans of adult South Africans were selected from the Oral and Dental Hospital, University of Pretoria, South Africa. In this study, the validation of the automatic landmarking was performed on 20 3D surfaces. INTRA-OE and INTER-OE were analyzed by registering 41 craniometric landmarks from 10 hard-tissue surfaces and 21 capulometric landmarks from 10 soft-tissue surfaces of the same individuals. Absolute precision of the landmark positioning (both on the samples as well as the template) was assessed by calculating the measurement error (ME) for each landmark over different observers. Systematic error (bias) and relative random error (precision) was further quantified through repeated measures ANOVA (ANOVA-RM). The analysis showed that the random component of the ME in landmark positioning between the automatic observations were on average on par with the manual observations, except for the soft-tissue landmarks where automatic landmarking showed lower ME compared to manual landmarking. No bias was observed within the craniometric landmarking methods, but some bias was observed for capulometric landmarking. In conclusion, this research provides a first validation of the precision and accuracy of the automatic placement of landmarks on 3D hard- and soft-tissue surfaces and demonstrates its utilization as a convenient prerequisite for geometric morphometrics based shape analysis of the nasal complex.",
keywords = "African Continental Ancestry Group, Anatomic Landmarks, Cone-Beam Computed Tomography, Forensic Anthropology, Humans, Imaging, Three-Dimensional, Nose/anatomy & histology, Reproducibility of Results, South Africa",
author = "Ridel, {A F} and F Demeter and M Galland and L'abb{\'e}, {E N} and D Vandermeulen and Oettl{\'e}, {A C}",
note = "Copyright {\textcopyright} 2019 Elsevier B.V. All rights reserved.",
year = "2020",
doi = "10.1016/j.forsciint.2019.110095",
language = "English",
volume = "306",
journal = "Forensic Science International",
issn = "0379-0738",
publisher = "Elsevier Ireland Ltd",

}

RIS

TY - JOUR

T1 - Automatic landmarking as a convenient prerequisite for geometric morphometrics. Validation on cone beam computed tomography (CBCT)- based shape analysis of the nasal complex

AU - Ridel, A F

AU - Demeter, F

AU - Galland, M

AU - L'abbé, E N

AU - Vandermeulen, D

AU - Oettlé, A C

N1 - Copyright © 2019 Elsevier B.V. All rights reserved.

PY - 2020

Y1 - 2020

N2 - Manual landmarking is used in several manual and semi-automated prediction guidelines for approximation of the nose. The manual placement of landmarks may, however, render the analysis less repeatable due to observer subjectivity and, consequently, have an impact on the accuracy of the human facial approximation. In order to address this subjectivity and thereby improve facial approximations, we are developing an automated three-dimensional (3D) method based on an automatic dense landmarking procedure using non-rigid surface registration. The aim of this study was to validate the automatic landmarking method by comparing the intra-observer errors (INTRA-OE) and inter-observer errors (INTER-OE) between automatic and manual landmarking. Cone beam computed tomography (CBCT) scans of adult South Africans were selected from the Oral and Dental Hospital, University of Pretoria, South Africa. In this study, the validation of the automatic landmarking was performed on 20 3D surfaces. INTRA-OE and INTER-OE were analyzed by registering 41 craniometric landmarks from 10 hard-tissue surfaces and 21 capulometric landmarks from 10 soft-tissue surfaces of the same individuals. Absolute precision of the landmark positioning (both on the samples as well as the template) was assessed by calculating the measurement error (ME) for each landmark over different observers. Systematic error (bias) and relative random error (precision) was further quantified through repeated measures ANOVA (ANOVA-RM). The analysis showed that the random component of the ME in landmark positioning between the automatic observations were on average on par with the manual observations, except for the soft-tissue landmarks where automatic landmarking showed lower ME compared to manual landmarking. No bias was observed within the craniometric landmarking methods, but some bias was observed for capulometric landmarking. In conclusion, this research provides a first validation of the precision and accuracy of the automatic placement of landmarks on 3D hard- and soft-tissue surfaces and demonstrates its utilization as a convenient prerequisite for geometric morphometrics based shape analysis of the nasal complex.

AB - Manual landmarking is used in several manual and semi-automated prediction guidelines for approximation of the nose. The manual placement of landmarks may, however, render the analysis less repeatable due to observer subjectivity and, consequently, have an impact on the accuracy of the human facial approximation. In order to address this subjectivity and thereby improve facial approximations, we are developing an automated three-dimensional (3D) method based on an automatic dense landmarking procedure using non-rigid surface registration. The aim of this study was to validate the automatic landmarking method by comparing the intra-observer errors (INTRA-OE) and inter-observer errors (INTER-OE) between automatic and manual landmarking. Cone beam computed tomography (CBCT) scans of adult South Africans were selected from the Oral and Dental Hospital, University of Pretoria, South Africa. In this study, the validation of the automatic landmarking was performed on 20 3D surfaces. INTRA-OE and INTER-OE were analyzed by registering 41 craniometric landmarks from 10 hard-tissue surfaces and 21 capulometric landmarks from 10 soft-tissue surfaces of the same individuals. Absolute precision of the landmark positioning (both on the samples as well as the template) was assessed by calculating the measurement error (ME) for each landmark over different observers. Systematic error (bias) and relative random error (precision) was further quantified through repeated measures ANOVA (ANOVA-RM). The analysis showed that the random component of the ME in landmark positioning between the automatic observations were on average on par with the manual observations, except for the soft-tissue landmarks where automatic landmarking showed lower ME compared to manual landmarking. No bias was observed within the craniometric landmarking methods, but some bias was observed for capulometric landmarking. In conclusion, this research provides a first validation of the precision and accuracy of the automatic placement of landmarks on 3D hard- and soft-tissue surfaces and demonstrates its utilization as a convenient prerequisite for geometric morphometrics based shape analysis of the nasal complex.

KW - African Continental Ancestry Group

KW - Anatomic Landmarks

KW - Cone-Beam Computed Tomography

KW - Forensic Anthropology

KW - Humans

KW - Imaging, Three-Dimensional

KW - Nose/anatomy & histology

KW - Reproducibility of Results

KW - South Africa

U2 - 10.1016/j.forsciint.2019.110095

DO - 10.1016/j.forsciint.2019.110095

M3 - Journal article

C2 - 31841934

VL - 306

JO - Forensic Science International

JF - Forensic Science International

SN - 0379-0738

M1 - 110095

ER -

ID: 238526856