Repeatability Characterisation and Error Budget of a Consumer Structured-Light Scanner for 3-D Wound Geometry:A Rigid-Phantom Study
2026-08-31 • Computer Vision and Pattern Recognition
Computer Vision and Pattern Recognition
AI summaryⓘ
The authors studied how much error occurs when using a consumer handheld 3D scanner to measure wound shapes. They found that repeated scans of the same unchanging wound model can show large variation, with surface area measurements sometimes differing widely. Most measurement differences come from how much of the wound surface the user captures, not from the scanner itself. Improving the scanner would likely not reduce errors much because the main problem is inconsistent scanning coverage. Their analysis also shows that standard methods of processing and comparing scans struggle to reliably measure wound size changes important for clinical use.
structured-light scannermeasurement errorrepeatabilityintraclass correlationsurface areawound care phantom3D reconstructionerror budgetscan repeatabilityoutlier removal
Authors
Pushkal Kumar, Aadit Aggarwal, Karlen Aleksanyan
Abstract
We characterise the measurement error of a free- hand consumer structured-light scanner used to derive three- dimensional geometric wound descriptors. Rigid wound-care phantoms cannot change, so every difference between repeat scans of one site is measurement error; all repeats come from a single scanner unit, nine sites and 23 scans, so this charac- terises one instrument. The 95 percent repeatability limit for reconstructed surface area is a factor of 4.8, with a confidence interval from 3.0 to 7.0, so rescanning an unchanged site can shift the reading from a 79 percent decrease to a 377 percent increase. Forty-four of 45 descriptors fall below an intraclass correlation of 0.50, and none of 248 descriptor and pipeline combinations reaches 0.75. An error budget formed by holding the analy- sis region fixed, leaving sensor and reconstruction untouched, bounds the share of variance attributable to how much surface the operator captured at 75 percent for surface area, 91 percent for hull area and 95 percent for bounding-box diagonal; only hull volume is majority instrumental, at 48 percent, so a better sensor would buy little. No wound is delineated anywhere in the chain, so the comparison against the four-week area reduction used clinically to predict healing, a ratio near 2.1, is a lower bound on the noise an unsegmented pipeline must overcome, not a measurement of wound-area reproducibility. Standardising the analysis region cuts the limit to 2.13, meeting that ratio rather than clearing it. Statistical outlier removal imposes a measured systematic area deficit near 11 percent.