Capturing data from three-dimensional surfaces using fuzzy landmarks

Abstract

Anatomical landmarks are defined as biologically meaningful loci that can be unambiguously defined and repeatedly located with a high degree of accuracy and precision. The neurocranial surface is characteristically void of such loci. We define a new class of landmarks, termed fuzzy landmarks, that will allow us to represent the form of the neurocranium. A fuzzy landmark represents the position of a biological structure that is precisely delineated, but occupies an area that is larger than a single point in the observer's reference system. In this study, we present a test case in which the cranial bosses are evaluated as fuzzy landmarks. Five fuzzy landmarks (the cranial bosses) and three traditional landmarks were placed repeatedly by a single observer on three-dimensional (3D) computed tomography (CT) surface reconstructions of pediatric dry skulls and skulls of pediatric patients, and directly on four of the same dry skulls using a 3Space digitizer. Thirty landmark digitizing trials from CT scans show an average error of 1.15 mm local to each fuzzy landmark, while the average error for the last ten trials was 0.75 mm, suggesting a learning curve. Data collected with the 3Space digitizer was comparable. Measurement error of fuzzy landmarks is larger than that of traditional landmarks, but is acceptable, especially since fuzzy landmarks allow inclusion of areas that would otherwise go unsampled. The information obtained is valuable in growth studies, clinical evaluation, and volume measurements. Our method of fuzzy landmarking is not limited to cranial bosses, and can be applied to any other anatomical features with fuzzy boundaries.

Measurement error in μCT‐based three‐dimensional geometric morphometrics introduced by surface generation and landmark data acquisition

“…A similar learning effect has been reported by Valeri et al. (). As with inter‐observer error reduction, including a training period seems to be an effective way of decreasing intra‐observer error, too (also see Chang & Alfaro, ).…”

Estimation of stature from femur length measured using computed tomography after the analysis of three-dimensional characteristics of femur bone in Korean cadavers

“…This is similar to the classic method using an osteometric board [20]. As in previous studies, the measurements using CT images were comparable to the measurements using an osteometric board [13,27,28]. All values are rounded off to the second decimal points H1x x-coordinate of proximal contact point after projecting on the horizontal plane, H1y y-coordinate of proximal contact point after projecting on the horizontal plane, H1z z-coordinate of proximal contact point after projecting on the horizontal plane, H2x x-coordinate of distal contact point after projecting on the horizontal plane, H2y ycoordinate of distal contact point after projecting on the horizontal plane, H2z z-coordinate of distal contact point after projecting on the horizontal plane CAD data was used to determine the reason that the measurements were similar.…”

Comparison of Mandibular Phenotypic and Genetic Integration between Baboon and Mouse

“…2, Table 1). We evaluated measurement error of landmark placement using established methods (Valeri et al 1998). Measurement error was further minimized by landmarking each mandible twice, checking for gross errors such as side reversal, and using the average of the two data collection trials in analyses.…”