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Measurement error using a SeeMaLab structured light 3D scanner against a Microscribe 3D digitizer
Dolores Messer1, Michelle S Svendsen2, Anders Galatius3
1Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, Denmark.
Peerj
|September 6, 2021
Summary
Structured light scanners offer precision comparable to digitizer arms in geometric morphometrics. While both methods have errors, scanners provide detailed 3D models and may reduce between-operator error, making them suitable for complex studies.
Area of Science:
- Geometric morphometrics
- 3D imaging technologies
- Comparative morphology
Background:
- Geometric morphometrics quantifies shape variation using landmark data.
- 3D digitizer arms and structured light surface scanners are portable tools for this field.
- This study compares a SeeMaLab structured light scanner to a Microscribe 3D digitizer arm.
Purpose of the Study:
- To assess measurement error and bias between a structured light scanner and a digitizer arm.
- To compare the precision and reliability of landmark data acquisition using both devices.
- To investigate the impact of operator and device on morphological measurements.
Main Methods:
- 31 anatomical landmarks were placed on 22 grey seal skulls using both a digitizer and a structured light scanner.
- Each skull was scanned twice, with landmarks annotated twice by two operators for each device.
- Procrustes ANOVAs were used to analyze within- and between-operator error, device-induced error, and scanning-related error.
Main Results:
- Both devices achieved similar precision, with the scanner potentially offering higher precision if difficult landmarks are excluded.
- Between-operator error was smaller with the scanner, though systematic differences between devices were observed, primarily at less defined landmarks.
- Device, operator, and landmark replica were significant but minor sources of variation compared to biological variation.
Conclusions:
- Structured light scanners are recommended when detailed 3D models are beneficial, offering comparable precision to digitizers.
- Pre-study identification of difficult landmarks is crucial for maximizing precision.
- Data from different devices/operators should not be combined without validation due to potential bias, especially with low biological variation.
- Scanner pipelines are better suited for studies involving multiple operators, with minimal scanning-related error when protocols are followed.
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