Automated Detection of 3D Landmarks for the Elimination of Non-Biological Variation in Geometric Morphometric Analyses

D Aneja; SR Vora; E D Camci; LG Shapiro; TC Cox

doi:10.1109/CBMS.2015.86

Automated Detection of 3D Landmarks for the Elimination of Non-Biological Variation in Geometric Morphometric Analyses

D Aneja, SR Vora, E D Camci, LG Shapiro, TC Cox

Anatomy & Developmental Biology

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

11 Citations (Scopus)

Abstract

Landmark-based morphometric analyses are used by anthropologists, developmental and evolutionary biologists to understand shape and size differences (eg. in the cranioskeleton) between groups of specimens. The standard, labor intensive approach is for researchers to manually place landmarks on 3D image datasets. As landmark recognition is subject to inaccuracies of human perception, digitization of landmark coordinates is typically repeated (often by more than one person) and the mean coordinates are used. In an attempt to improve efficiency and reproducibility between researchers, we have developed an algorithm to locate landmarks on CT mouse hemi-mandible data. The method is evaluated on 3D meshes of 28-day old mice, and results compared to landmarks manually identified by experts. Quantitative shape comparison between two inbred mouse strains demonstrate that data obtained using our algorithm also has enhanced statistical power when compared to data obtained by manual landmarking.

Original language	English
Title of host publication	IEEE 28th International Symposium on Computer-Based Medical Systems (CBMS 2015)
Editors	C Traina Jr, P P Rodrigues, B Kane, P M de Azevedo Marques, A J M Traina
Place of Publication	Piscataway NJ USA
Publisher	IEEE Computer Society
Pages	78-83
Number of pages	6
ISBN (Print)	9781467367752
DOIs	https://doi.org/10.1109/CBMS.2015.86
Publication status	Published - 2015
Event	IEEE International Symposium on Computer Based Medical Systems (CBMS) 2015 - University of São Paulo, São Paulo, Brazil Duration: 22 Jun 2015 → 25 Jun 2016 Conference number: 28th https://ieeexplore.ieee.org/xpl/conhome/7164867/proceeding (Proceedings)

Conference

Conference	IEEE International Symposium on Computer Based Medical Systems (CBMS) 2015
Abbreviated title	CBMS 2015
Country/Territory	Brazil
City	São Paulo
Period	22/06/15 → 25/06/16
Internet address	https://ieeexplore.ieee.org/xpl/conhome/7164867/proceeding (Proceedings)

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10.1109/CBMS.2015.86

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Aneja, D., Vora, SR., Camci, E. D., Shapiro, LG., & Cox, TC. (2015). Automated Detection of 3D Landmarks for the Elimination of Non-Biological Variation in Geometric Morphometric Analyses. In C. Traina Jr, P. P. Rodrigues, B. Kane, P. M. de Azevedo Marques, & A. J. M. Traina (Eds.), IEEE 28th International Symposium on Computer-Based Medical Systems (CBMS 2015) (pp. 78-83). IEEE Computer Society. https://doi.org/10.1109/CBMS.2015.86

Aneja, D ; Vora, SR ; Camci, E D et al. / Automated Detection of 3D Landmarks for the Elimination of Non-Biological Variation in Geometric Morphometric Analyses. IEEE 28th International Symposium on Computer-Based Medical Systems (CBMS 2015). editor / C Traina Jr ; P P Rodrigues ; B Kane ; P M de Azevedo Marques ; A J M Traina. Piscataway NJ USA : IEEE Computer Society, 2015. pp. 78-83

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title = "Automated Detection of 3D Landmarks for the Elimination of Non-Biological Variation in Geometric Morphometric Analyses",

abstract = "Landmark-based morphometric analyses are used by anthropologists, developmental and evolutionary biologists to understand shape and size differences (eg. in the cranioskeleton) between groups of specimens. The standard, labor intensive approach is for researchers to manually place landmarks on 3D image datasets. As landmark recognition is subject to inaccuracies of human perception, digitization of landmark coordinates is typically repeated (often by more than one person) and the mean coordinates are used. In an attempt to improve efficiency and reproducibility between researchers, we have developed an algorithm to locate landmarks on CT mouse hemi-mandible data. The method is evaluated on 3D meshes of 28-day old mice, and results compared to landmarks manually identified by experts. Quantitative shape comparison between two inbred mouse strains demonstrate that data obtained using our algorithm also has enhanced statistical power when compared to data obtained by manual landmarking.",

author = "D Aneja and SR Vora and Camci, {E D} and LG Shapiro and TC Cox",

year = "2015",

doi = "10.1109/CBMS.2015.86",

language = "English",

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pages = "78--83",

editor = "{Traina Jr}, C and Rodrigues, {P P} and B Kane and {de Azevedo Marques}, {P M} and Traina, {A J M}",

booktitle = "IEEE 28th International Symposium on Computer-Based Medical Systems (CBMS 2015)",

publisher = "IEEE Computer Society",

address = "United States of America",

note = "IEEE International Symposium on Computer Based Medical Systems (CBMS) 2015, CBMS 2015 ; Conference date: 22-06-2015 Through 25-06-2016",

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Aneja, D, Vora, SR, Camci, ED, Shapiro, LG & Cox, TC 2015, Automated Detection of 3D Landmarks for the Elimination of Non-Biological Variation in Geometric Morphometric Analyses. in C Traina Jr, PP Rodrigues, B Kane, PM de Azevedo Marques & AJM Traina (eds), IEEE 28th International Symposium on Computer-Based Medical Systems (CBMS 2015). IEEE Computer Society, Piscataway NJ USA, pp. 78-83, IEEE International Symposium on Computer Based Medical Systems (CBMS) 2015, São Paulo, Brazil, 22/06/15. https://doi.org/10.1109/CBMS.2015.86

Automated Detection of 3D Landmarks for the Elimination of Non-Biological Variation in Geometric Morphometric Analyses. / Aneja, D; Vora, SR; Camci, E D et al.

IEEE 28th International Symposium on Computer-Based Medical Systems (CBMS 2015). ed. / C Traina Jr; P P Rodrigues; B Kane; P M de Azevedo Marques; A J M Traina. Piscataway NJ USA : IEEE Computer Society, 2015. p. 78-83.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

T1 - Automated Detection of 3D Landmarks for the Elimination of Non-Biological Variation in Geometric Morphometric Analyses

AU - Aneja, D

AU - Vora, SR

AU - Camci, E D

AU - Shapiro, LG

AU - Cox, TC

N1 - Conference code: 28th

PY - 2015

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N2 - Landmark-based morphometric analyses are used by anthropologists, developmental and evolutionary biologists to understand shape and size differences (eg. in the cranioskeleton) between groups of specimens. The standard, labor intensive approach is for researchers to manually place landmarks on 3D image datasets. As landmark recognition is subject to inaccuracies of human perception, digitization of landmark coordinates is typically repeated (often by more than one person) and the mean coordinates are used. In an attempt to improve efficiency and reproducibility between researchers, we have developed an algorithm to locate landmarks on CT mouse hemi-mandible data. The method is evaluated on 3D meshes of 28-day old mice, and results compared to landmarks manually identified by experts. Quantitative shape comparison between two inbred mouse strains demonstrate that data obtained using our algorithm also has enhanced statistical power when compared to data obtained by manual landmarking.

AB - Landmark-based morphometric analyses are used by anthropologists, developmental and evolutionary biologists to understand shape and size differences (eg. in the cranioskeleton) between groups of specimens. The standard, labor intensive approach is for researchers to manually place landmarks on 3D image datasets. As landmark recognition is subject to inaccuracies of human perception, digitization of landmark coordinates is typically repeated (often by more than one person) and the mean coordinates are used. In an attempt to improve efficiency and reproducibility between researchers, we have developed an algorithm to locate landmarks on CT mouse hemi-mandible data. The method is evaluated on 3D meshes of 28-day old mice, and results compared to landmarks manually identified by experts. Quantitative shape comparison between two inbred mouse strains demonstrate that data obtained using our algorithm also has enhanced statistical power when compared to data obtained by manual landmarking.

UR - http://www.ncbi.nlm.nih.gov/pubmed/26258171

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DO - 10.1109/CBMS.2015.86

M3 - Conference Paper

SN - 9781467367752

SP - 78

EP - 83

BT - IEEE 28th International Symposium on Computer-Based Medical Systems (CBMS 2015)

A2 - Traina Jr, C

A2 - Rodrigues, P P

A2 - Kane, B

A2 - de Azevedo Marques, P M

A2 - Traina, A J M

PB - IEEE Computer Society

CY - Piscataway NJ USA

T2 - IEEE International Symposium on Computer Based Medical Systems (CBMS) 2015

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ER -

Aneja D, Vora SR, Camci ED, Shapiro LG, Cox TC. Automated Detection of 3D Landmarks for the Elimination of Non-Biological Variation in Geometric Morphometric Analyses. In Traina Jr C, Rodrigues PP, Kane B, de Azevedo Marques PM, Traina AJM, editors, IEEE 28th International Symposium on Computer-Based Medical Systems (CBMS 2015). Piscataway NJ USA: IEEE Computer Society. 2015. p. 78-83 https://doi.org/10.1109/CBMS.2015.86

Automated Detection of 3D Landmarks for the Elimination of Non-Biological Variation in Geometric Morphometric Analyses

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