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Gradient vector flow snake method for quantitative image reconstruction applied to mandibular distraction surgery

Articolo
Data di Pubblicazione:
2009
Abstract:
To improve planning of maxillofacial surgery, a novel method for maxillary-, mandibular-, and facial-nerve 3-D image reconstruction was implemented and optimized. A set of images acquired by a computed tomography (CT) scanner was segmented to reconstruct the 3-D model of the maxilla and mandible. Particular attention was given to the segmentation of the facial nerve, which was obtained through the gradient-vector-flow (GVF) snake method. After segmentation, precise anatomical 3-D plastic models were fabricated through stereolithography from CT scans of five clinical cases that will undergo either dental implant surgery or bone distraction. For all cases, 3-D models delivered essential visual and tactile information for the planning and simulation of surgery as well as for customized implant preparation.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Biomedical image processing; image edge analysis; image enhancement; image reconstruction; image segmentation
Elenco autori:
Ravazzani, PAOLO GIUSEPPE; Grandori, Ferdinando; Tognola, Gabriella; Parazzini, Marta
Autori di Ateneo:
PARAZZINI MARTA
RAVAZZANI PAOLO GIUSEPPE
TOGNOLA GABRIELLA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/47430
Pubblicato in:
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
Journal
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