How does scanner choice and 3D model resolution affect data accuracy?

Abstract

Researchers using digital methods often collect data from 3D models at different resolutions, obtained using different scanning techniques. Although previous research has sought to understand whether scanning method and model resolution affect data accuracy, no study has systematically evaluated the sources of error associated with scanning method, data acquisition method and model resolution with the aim of providing practical recommendations about the model resolution required to yield sufficiently accurate data for specimens of given sizes. In this study, using data taken from primate specimens of three broad size categories, we test whether 3D models obtained using five different scanners (Breuckmann SmartSCAN, DAVID/HP 3D Pro S3, NextEngine 2020i, Creaform Go!Scan 20 and microCT/clinicalCT) yield accurate measurements. We assess whether caliper measurements can be used alongside measurements collected from 3D surface models, whether scanning resolution affects measurement accuracy, and how scan resolution, estimated using each scanner's proprietary software, compares to model resolution measured in a standardized way. Each scanner produces 3D models that yield accurate measurements for each size category, however, combining caliper data with those taken from digital models can be problematic. Our results indicate that the accuracy of measurements taken from 3D models depends on both object size and model resolution. Based on our findings, we recommend that small specimens should be scanned at <0.3 mm, medium specimens at 0.3–0.7 mm, and large specimens at 0.3–0.5 mm resolutions if data taken from 3D surface models are to be combined with caliper datasets. We further show, for the first time, that discrepancies in estimated final model resolution are frequently observed across software packages. We therefore recommend that researchers ensure that final model resolutions are adequate based on specimen size and are independently verified using a software package other than the scanner's proprietary software. Finally, we consider the implications of the findings that measurements obtained from surface models are variably consistent with those obtained using calipers.

Facial asymmetry tracks genetic diversity amongGorillasubspecies

“…The remaining 92 models were reconstructed from medical CT scans at the Katholieke Universiteit Leuven, Belgium (Siemens Sensation 64, 120 kV, 135 mA, 1 mm slice thickness, reconstruction interval of 0.5 mm, 15 cm field of view, 0.29296875 mm pixel size, 512*512 pixel matrix) [ 25 ], and the Smithsonian's National Museum of Natural History (Washington, DC; Siemens Somatom Emotion CT Scanner, 110 kV, 70 mA, 1 mm slice thickness, 0.1 mm reconstruction increment; surface models generated in Materialize Mimics). A recent study suggests that there are no significant differences in models derived from different imaging modalities [ 26 ], allowing for the direct comparisons made here.…”

One Genus or Two? Evaluating Whether Gracile and Robust Capuchin Monkeys are Validly Classified as Separate Genera Based on Craniofacial Shape

“…All 3D models used have a scan resolution of <0.5 mm. Differences in how 3D models were generated are unlikely to have produced substantial measurement error (Balolia & Massey, 2021;Fruciano et al, 2017;Marcy et al, 2018).…”

Error intermétodo en morfometría geométrica y la relevancia de la texturización y el registro de los puntos homólogos

“…Se ha de tener en cuenta que la resolución del instrumento de digitalización es la característica principal que determina la calidad del modelo tridimensional (Tenova et al,2020). Pero no solo las diferencias que pueden observarse entre estas, sino que cada técnica presenta diferentes softwares, los cuales difieren en la forma en la cual se calcula la resolución del modelo 3D, pudiendo llegar a afectar la precisión de la medición (Balolia y Massey, 2021;Waltenberger et al, 2021;White et al, 2020).…”

“…Escenario que ha permitido generar colecciones digitales que, en ocasiones se han puesto a disposición de morfómetras y antropólogos a través de bases de datos. La creación de estas plataformas tiene una serie de ventajas, deja de ser necesario desplazarse para la toma de la muestra, con el consiguiente ahorro de tiempo y fondos; así como, se contribuye a la preservación al evitar la manipulación del material esquelético con la consiguiente degradación (Balolia y Massey, 2021;Buzi et al, 2018;Evin et al, 2016;Friess, 2012;Kullmer, 2008;Profico et al, 2018;Sforza, et al, 2013;Veneziano, et al, 2018;Waltenberger et al, 2021;Weber, 2015).…”

“…Hasta hace pocos años, los trabajos que prestaban atención al error en MG 3D eran escasos, fundamentalmente en el error intermétodo (Fourie et al, 2011;Fruciano, 2016;Robinson y Terhune, 2017;Ross y Willians, 2008). Sin embargo, esta tendencia se ha visto modificada durante el último lustro (Balolia y Massey, 2021;Buzi et al, 2018;Fox et al, 2020;Fruciano, 2016;Fruciano et al, 2017;Robinson y Ter-hune, 2017;Shearer et al, 2017;Toneva et al 2020;Waltenberg et al, 2021). Los análisis apuntan a bajos niveles de error cuando se emplean mecanismos diversos, pudiendo compatibilizarse el uso de archivos procedentes de diversas fuentes.…”