Consistency of selected craniometric landmark locations and the resulting variation in measurements

Standardization and quality assurance in skeletal landmark placement and osteometry

“…A similar study by Smith and Boaks [9] on the cranium also noted major discrepancies in landmark location. For instance, interorbital breadth was noted to be taken correctly (as specified by the definition) by only 48% of the study participants [9]. Measurement variability and error culminates in poor repeatability, which ultimately affects the confidence with which skeletal remains can be classified.…”

“…[8]. A similar study by Smith and Boaks [9] on the cranium also noted major discrepancies in landmark location. For instance, interorbital breadth was noted to be taken correctly (as specified by the definition) by only 48% of the study participants [9].…”

Deep learning and morphometric approach for Sex determination of the lumbar vertebrae in a Thai population

“…3,4,9,[15][16][17][18][19][20][21] Although morphometric methods are effective, they are highly dependent on the observer's experience to assess the parameters, and they can still be subject to measurement errors. 22 In recent years, deep learning (DL) has been increasingly included in various studies because it automatically extracts features from numerous images and then performs image classification. 23 Moreover, assessment from the deep-learning model is less time-consuming and more cost-effective.…”