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08:07
A Morphometric and Cellular Analysis Method for the Murine Mandibular Condyle
Published on: January 11, 2018
8.9K
Marker-based watershed transform method for fully automatic mandibular segmentation from CBCT images.
Yi Fan1,2, Richard Beare3,4, Harold Matthews2,5
11 Department of Dentistry, The University of Melbourne , Melbourne, VIC , Australia.
Dento Maxillo Facial Radiology
|November 1, 2018
Summary
This study presents an automated method for segmenting the mandible from CBCT images using marker-based watershed transform. The technique achieves high accuracy, comparable to manual segmentation, for improved dental imaging analysis.
Area of Science:
- Medical Imaging
- Radiology
- Computer-Aided Diagnosis
Background:
- Cone-beam computed tomography (CBCT) is crucial for dental imaging.
- Accurate mandible segmentation is essential for diagnosis and treatment planning.
- Manual segmentation is time-consuming and prone to inter-observer variability.
Purpose of the Study:
- To develop and validate a reliable, automated method for mandible segmentation from CBCT images.
- To compare the accuracy of the automated method against established interactive segmentation techniques.
Main Methods:
- Utilized a marker-based watershed transform algorithm on CBCT images.
- Generated a height map from the CBCT intensity gradient to delineate boundaries.
- Employed image registration for automatic marker placement (mandible and background).
Main Results:
- Achieved a Dice similarity coefficient of 0.97 ± 0.01, indicating excellent overlap.
- Demonstrated boundary deviations predominantly under 1 mm.
- Identified minor segmentation errors in specific anatomical regions with minimal impact on overall morphology.
Conclusions:
- The marker-based watershed transform offers a practical and accurate automated solution for mandible segmentation.
- The method's accuracy is comparable to traditional interactive segmentation approaches.
- This automated technique has the potential to streamline dental imaging workflows.
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