PUMA
Istituto di Ingegneria Biomedica     
Tognola G., Parazzini M., Pedretti G., Ravazzani P., Grandori F., Pesatori A., Norgia M., Svelto C. Gradient vector flow snake method for quantitative image reconstruction applied to mandibular distraction surgery. In: Ieee Transactions on Instrumentation and Measurement, vol. 58 (7) pp. 2087 - 2093. IEEE, 2009.
 
 
Abstract
(English)
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
URL: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?isnumber=5071752&arnumber=4799157&count=39&index=5
DOI: 10.1109/TIM.2009.2015525
Subject biomedical image processing
biomedical measurements
image edge analysis
image enchancement
image reconstruction
image segmentation


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