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

Rundo, L.

Risultato della ricerca: Article

Abstract

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.
Lingua originaleEnglish
pagine (da-a)232-253
Numero di pagine22
RivistaINTERNATIONAL JOURNAL OF ADAPTIVE AND INNOVATIVE SYSTEMS
Volume2
Stato di pubblicazionePublished - 2015

Cita questo

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title = "An edge-driven 3D region-growing approach for upper airway morphology and volume evaluation in patients with Pierre Robin sequence",
abstract = "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 = "Pierre Robin sequence, multidetector CT, airways segmentation, region growing, 3D rendering, airway model reconstruction",
author = "{Rundo, L.} and Sergio Salerno and Cesare Gagliardo and Carmelo Militello and Salvatore Vitabile",
year = "2015",
language = "English",
volume = "2",
pages = "232--253",
journal = "INTERNATIONAL JOURNAL OF ADAPTIVE AND INNOVATIVE SYSTEMS",
issn = "1740-2107",

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TY - JOUR

T1 - An edge-driven 3D region-growing approach for upper airway morphology and volume evaluation in patients with Pierre Robin sequence

AU - Rundo, L.

AU - Salerno, Sergio

AU - Gagliardo, Cesare

AU - Militello, Carmelo

AU - Vitabile, Salvatore

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

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

UR - http://hdl.handle.net/10447/291810

M3 - Article

VL - 2

SP - 232

EP - 253

JO - INTERNATIONAL JOURNAL OF ADAPTIVE AND INNOVATIVE SYSTEMS

JF - INTERNATIONAL JOURNAL OF ADAPTIVE AND INNOVATIVE SYSTEMS

SN - 1740-2107

ER -