Abstract
In this paper, a semi-automatic approach for segmentation of the upper airways isproposed. The implemented approach uses an edge-driven 3D region-growing algorithm to segment ROIs and 3D volume-rendering technique to reconstruct the 3D model of the upper airways. This method can be used to integrate information inside a medical decision support system, making it possible to enhance medical evaluation. The effectiveness of the proposed segmentation approach was evaluated using Jaccard (92.1733%) and dice (94.6441%) similarity indices and specificity (96.8895%) and sensitivity (97.6682%) rates.The proposed method achieved an average computation time reduced by a 16x factor with respect to manual segmentation.
Lingua originale | English |
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Numero di pagine | 22 |
Rivista | INTERNATIONAL JOURNAL OF ADAPTIVE AND INNOVATIVE SYSTEMS |
Stato di pubblicazione | Published - 2016 |