Evaluating causes of error in landmark-based data collection using scanners.

Abstract

In this study, we assess the precision, accuracy, and repeatability of craniodental landmarks (Types I, II, and III, plus curves of semilandmarks) on a single macaque cranium digitally reconstructed with three different surface scanners and a microCT scanner. Nine researchers with varying degrees of osteological and geometric morphometric knowledge landmarked ten iterations of each scan (40 total) to test the effects of scan quality, researcher experience, and landmark type on levels of intra- and interobserver error. Two researchers additionally landmarked ten specimens from seven different macaque species using the same landmark protocol to test the effects of the previously listed variables relative to species-level morphological differences (i.e., observer variance versus real biological variance). Error rates within and among researchers by scan type were calculated to determine whether or not data collected by different individuals or on different digitally rendered crania are consistent enough to be used in a single dataset. Results indicate that scan type does not impact rate of intra- or interobserver error. Interobserver error is far greater than intraobserver error among all individuals, and is similar in variance to that found among different macaque species. Additionally, experience with osteology and morphometrics both positively contribute to precision in multiple landmarking sessions, even where less experienced researchers have been trained in point acquisition. Individual training increases precision (although not necessarily accuracy), and is highly recommended in any situation where multiple researchers will be collecting data for a single project.

DOI: 10.1371/journal.pone.0187452

Cite this paper

@article{Shearer2017EvaluatingCO, title={Evaluating causes of error in landmark-based data collection using scanners.}, author={Brian M Shearer and Siobh{\'a}n B. Cooke and Lauren B Halenar and Samantha L Reber and Jeannette E Plummer and Eric Delson and Melissa Tallman}, journal={PloS one}, year={2017}, volume={12 11}, pages={e0187452} }