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.
|Numero di pagine||22|
|Rivista||INTERNATIONAL JOURNAL OF ADAPTIVE AND INNOVATIVE SYSTEMS|
|Stato di pubblicazione||Published - 2016|