6533b874fe1ef96bd12d617b

RESEARCH PRODUCT

An edge-driven 3D region-growing approach for upper airway morphology and volume evaluation in patients with Pierre Robin sequence

Carmelo MilitelloSalvatore VitabileLeonardo RundoCesare GagliardoSergio Salerno

subject

Pierre Robin sequence multidetector CT airways segmentation region growing 3D rendering airway model reconstruction

description

Abstract: Pierre Robin sequence (PRS) is a pathological condition responsible for a sequence of clinical events, such as breathing and feeding difficulties, that must be addressed to give the patient at least a chance to survive. By using medical imaging techniques, in a non-intrusive way, the surgeon has the opportunity to obtain 3D views, reconstruction of the regions of interest (ROIs), useful to increase understanding of the PRS patient’s condition. In this paper, a semi-automatic approach for segmentation of the upper airways is proposed. 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.

https://doi.org/10.1504/ijais.2015.074406