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

Authors: Carmelo Militello; Salvatore Vitabile; Leonardo Rundo; Cesare Gagliardo; Sergio Salerno

Addresses: Istituto di Bioimmagini e Fisiologia Molecolare (IBFM CNR), Consiglio Nazionale delle Ricerche, Contrada Pietrapollastra-Pisciotto, 90015, Cefalù, PA, Italy ' Dipartimento di Biopatologia e Biotecnologie Mediche (DIBIMED), Università degli Studi di Palermo, Via del Vespro, 90127, Palermo, Italy ' Istituto di Bioimmagini e Fisiologia Molecolare (IBFM CNR), Consiglio Nazionale delle Ricerche, Contrada Pietrapollastra-Pisciotto, 90015, Cefalù, PA, Italy ' Dipartimento di Biopatologia e Biotecnologie Mediche (DIBIMED), Università degli Studi di Palermo, Via del Vespro, 90127, Palermo, Italy ' Dipartimento di Biopatologia e Biotecnologie Mediche (DIBIMED), Università degli Studi di Palermo, Via del Vespro, 90127, Palermo, Italy

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.

Keywords: 3D region growing; edge-driven segmentation; airway segmentation; Pierre Robin sequence; PRS; 3D modelling; medical DSS; decision support systems; MDSS; upper airway morphology; volume evaluation; breathing difficulties; feeding difficulties; medical imaging; regions of interest; ROIs; image segmentation; healthcare technology.

DOI: 10.1504/IJAIS.2015.074406

International Journal of Adaptive and Innovative Systems, 2015 Vol.2 No.3, pp.232 - 253

Available online: 27 Jan 2016 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article