39 research outputs found
Schematic overview of the segmentation algorithm.
<p>The faulty outline of the thresholded condyle is clearly present (A). The user selects a seed-point once every five slides. The selection of this seed point automatically renders an outline of the condyle based on the threshold (B). The user can adjust the threshold interactively to generate the best fit for the condylar outline. All threshold values are plotted in a graph (C). For all slides in between the two user defined slides, the threshold value is determined through interpolation. Subsequently, the region growing is initiated, after which post processing is possible. Finally, the condyle is segmented and rendered in 3D (D).</p
A Novel Region-Growing Based Semi-Automatic Segmentation Protocol for Three-Dimensional Condylar Reconstruction Using Cone Beam Computed Tomography (CBCT)
<div><p>Objective</p><p>To present and validate a semi-automatic segmentation protocol to enable an accurate 3D reconstruction of the mandibular condyles using cone beam computed tomography (CBCT).</p><p>Materials and Methods</p><p>Approval from the regional medical ethics review board was obtained for this study. Bilateral mandibular condyles in ten CBCT datasets of patients were segmented using the currently proposed semi-automatic segmentation protocol. This segmentation protocol combined 3D region-growing and local thresholding algorithms. The segmentation of a total of twenty condyles was performed by two observers. The Dice-coefficient and distance map calculations were used to evaluate the accuracy and reproducibility of the segmented and 3D rendered condyles.</p><p>Results</p><p>The mean inter-observer Dice-coefficient was 0.98 (range [0.95–0.99]). An average 90<sup>th</sup> percentile distance of 0.32 mm was found, indicating an excellent inter-observer similarity of the segmented and 3D rendered condyles. No systematic errors were observed in the currently proposed segmentation protocol.</p><p>Conclusion</p><p>The novel semi-automated segmentation protocol is an accurate and reproducible tool to segment and render condyles in 3D. The implementation of this protocol in the clinical practice allows the CBCT to be used as an imaging modality for the quantitative analysis of condylar morphology.</p></div
A 3D rendered virtual head model of a patient from Maxilim, reconstructed from the original CBCT data.
<p>The inaccurate reconstruction of the condyle is clearly visible. No measurement of the condylar shape or volume can be made due to the discontinuity of the condylar surface.</p
Descriptive statistics of condylar volume.
<p>Standard deviation (SD).</p><p>Descriptive statistics of condylar volume.</p
A typical 3D distance map of the manually and semi-automatically segmented condyles.
<p>The green area indicates the surface of the manually segmented condyle whereas the red area indicates the surface of semi-automatically segmented condyle. The colour intensity quantifies the distance between both surfaces. Only small differences are present between both surfaces.</p
Median, 90<sup>th</sup> percentile and range of surface errors of 3D rendered condyles between the three groups (distance map).
<p>Median, 90<sup>th</sup> percentile and range of surface errors of 3D rendered condyles between the three groups (distance map).</p
The 3D reconstruction of semi-automatically segmented condyle (red), and its integration into the original 3D virtual head model of <b>Figure 1</b>.
<p>Condylar measurements can be carried out using this integrated model.</p
Illustrating step 5.
<p>A reference frame is set up. The subnasal landmark (Sn) is indicated through which a plane, perpendicular to the horizontal plane of the reference frame, is computed. The new plane is used to split the (in step 4 computed) distance map. (The individual in this photograph has given written informed consent (as outlined in PLOS consent form) to publish this picture).</p
Histogram of the number of persons per category based on the 95<sup>th</sup> percentile.
<p>Histogram of the number of persons per category based on the 95<sup>th</sup> percentile.</p
The asymmetry of the lower face in patients and controls.
<p>The asymmetry of the lower face in patients and controls.</p