Abstract
Sialography Cone-Beam Computerized Tomography (Sialo-CBCT) imaging is commonly used for the assesment and diagnosis of salivary gland pathologies. Since the examination of the Sialo-CBCT scans is challenging due to the salivary ducts complexity, oral radiologists perform their evaluation on 2D Maximum Intensity Projection images. This results in a mostly qualitative, incomplete, and observer-dependent analysis. We present the first fully automatic method for the segmentation and comprehensive quantitative structural analysis of the parotid salivary ducts in Sialo-CBCT scans. It consists of: 1) segmentation of the primary and secondary ducts; 2) computation of a 3D tree model of the salivary gland; 3) quantitative analysis of the salivary glands features, and; 4) visualization of the tree model and analysis results. We describe a new evaluation methodology for the validation of the salivary ducts model without ground-truth manual delineation. Experimental studies on 62 Sialo-CT scans show that our method successfully identifies 93% and 86% of the primary salivary ducts and the 1st and 2nd order duct branches and bifurcations. The RSME of the primary duct diameter is 0.33 mm (std = 0.04). Our method may be useful for the characterization of salivary gland architecture and for the diagnosis of ductal pathologies.
Original language | English |
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Pages (from-to) | 488-499 |
Number of pages | 12 |
Journal | Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization |
Volume | 9 |
Issue number | 5 |
DOIs | |
State | Published - 2021 |
Bibliographical note
Publisher Copyright:© 2021 Informa UK Limited, trading as Taylor & Francis Group.
Keywords
- Segmentation
- Sialo-CBCT scans
- modelling
- salivary gland imaging
- sialography