Segmentation of facial bone surfaces by patch growing from cone beam CT volumes

Abstract

Objectives: The motivation behind this work was to design an automatic algorithm capable of segmenting the exterior of the dental and facial bones including the mandible, teeth, maxilla and zygomatic bone with an open surface (a surface with a boundary) from CBCT images for the anatomy-based reconstruction of radiographs. Such an algorithm would provide speed, consistency and improved image quality for clinical workflows, for example, in planning of implants. Methods: We used CBCT images from two studies: first to develop (n 5 19) and then to test (n 5 30) a segmentation pipeline. The pipeline operates by parameterizing the topology and shape of the target, searching for potential points on the facial bone-soft tissue edge, reconstructing a triangular mesh by growing patches on from the edge points with good contrast and regularizing the result with a surface polynomial. This process is repeated for convergence. Results: The output of the algorithm was benchmarked against a hand-drawn reference and reached a 0.50 ± 1.0-mm average and 1.1-mm root mean squares error in Euclidean distance from the reference to our automatically segmented surface. These results were achieved with images affected by inhomogeneity, noise and metal artefacts that are typical for dental CBCT. Conclusions: Previously, this level of accuracy and precision in dental CBCT has been reported in segmenting only the mandible, a much easier target. The segmentation results were consistent throughout the data set and the pipeline was found fast enough (,1-min average computation time) to be considered for clinical use.

Geometric accuracy of magnetic resonance imaging–derived virtual 3‐dimensional bone surface models of the mandible in comparison to computed tomography and cone beam computed tomography: A porcine cadaver study

“…However, CBCT is known for lower signal-to-noise ratios, worse contrast, and higher-intensity inhomogeneity than conventional CT, making the DICOM to 3-dimensional surface model conversion more troublesome compared with CT imaging. [43][44][45][46] A similar experience was had in this study, with the CBCT images the most difficult to segment. When discussing the data presented here, it is important to note that the use of other segmentation protocols for the respective imaging methods might have had a significant impact on the accuracy of the derived 3-dimensional models.…”

“…46 While CT represents the gold standard for CAD/CAM procedures, the thresholding of bone-specific gray values is less straightforward in CBCT images. [43][44][45][46] This aspect is reflected in the present study, where the segmentation of CBCT images required individual and local thresholding followed by sometimes extensive manual postprocessing. In contrast, CT imaging was performed by global thresholding without the need for manual post-processing.…”

Objective Analysis of Facial Bone Computed Tomography Images Using Curvature Measurement

“…Reconstructed 3D CT images based on section slices cannot show a perfect curve, and the unintended aws could affect the resulting values. Recent studies have presented curvature estimation and segmentation techniques to account for breaks in curves, and favorable results have been demonstrated 2,10,13 . Our group is planning to implement appropriate strategies to resolve this limitation.…”

“…The facial skeleton consists of multiple convoluted bony segments, and injury can be diagnosed using various imaging methods 1 . In contrast to the analysis of other long bones, the structural characteristics of facial bone increase the di culty of the diagnostic process 2 . In case of long bone injuries, such as hand fractures, biomechanical studies can be used to analyze recovery of the fracture site 3 .…”

Objective analysis of facial bone fracture CT images using curvature measurement in a surface mesh model

“…The facial skeleton consists of multiple convoluted bony segments, and injury can be diagnosed using various imaging methods 1 . In contrast to the analysis of other long bones, the structural characteristics of facial bone increase the difficulty of the diagnostic process 2 . In case of long bone injuries, such as hand fractures, biomechanical studies can be used to analyze the recovery of the fracture site 3 .…”