Marker-based watershed transform method for fully automatic mandibular segmentation from CBCT images.

Objectives:: To propose a reliable and practical method for automatically segmenting the mandible from CBCT images.

Methods:: The marker-based watershed transform is a region-growing approach that dilates or "floods" predefined markers onto a height map whose ridges denote object boundaries. We applied this method to segment the mandible from the rest of the CBCT image. The height map was generated to enhance the sharp decreases of intensity at the mandible/tissue border and suppress noise by computing the intensity gradient image of the CBCT itself. Two sets of markers, "mandible" and "background" were automatically placed inside and outside the mandible, respectively in a novel image using image registration. The watershed transform flooded the gradient image by dilating the markers simultaneously until colliding at watershed lines, estimating the mandible boundary. CBCT images of 20 adolescent subjects were chosen as test cases. Segmentation accuracy of the proposed method was evaluated by measuring overlap (Dice similarity coefficient) and boundary agreement against a well-accepted interactive segmentation method described in the literature.

Results:: The Dice similarity coefficient was 0.97 ± 0.01 (mean ± SD), indicating almost complete overlap between the automatically and the interactively segmented mandibles. Boundary deviations were predominantly under 1 mm for most of the mandibular surfaces. The errors were mostly from bones around partially erupted wisdom teeth, the condyles and the dental enamels, which had minimal impact on the overall morphology of the mandible.

Conclusions:: The marker-based watershed transform method produces segmentation accuracy comparable to the well-accepted interactive segmentation approach.