A computer-aided method for scoliosis fusion level selection by a topologically ordered self organizing Kohonen network [r-libre/429]

Mezghani, Neila; Phan, Philippe; Mitiche, Amar; Labelle, Hubert et De Guise, Jacques A. (2010). A computer-aided method for scoliosis fusion level selection by a topologically ordered self organizing Kohonen network. Dans Proceedings of the 20th IEEE International Conference on Pattern Recognition (ICPR) (p. 4012-4015). IEEE. https://doi.org/10.1109/ICPR.2010.976

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Catégorie de document :	Communications dans des actes de congrès/colloques
Évaluation par un comité de lecture :	Oui
Étape de publication :	Publié
Résumé :	Surgical instrumentation for the Adolescent idiopathic scoliosis (AIS) is a complex procedure involving many difficult decisions. Selection of the appropriate fusion level remains one of the most challenging decisions in scoliosis surgery. Currently, the Lenke classification model is generally followed in surgical planning. The purpose of our study is to investigate a computer aided method for Lenke classification and scoliosis fusion level selection. The method uses a self organizing neural network trained on a large database of surgically treated AIS cases. The neural network produces two maps, one of Lenke classes and the other of fusion levels. These two maps show that the Lenke classes are associated with the the proper fusion level categories everywhere in the map except at the Lenke class transitions. The topological ordering of the Cobb angles in the neural network justifies determining a patient scoliotic treatment instrumentation using directly the fusion level map rather than via the Lenke classification.
Adresse de la version officielle :	http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arn...
Déposant:	Mezghani, Neila
Responsable :	Neila Mezghani
Dépôt :	24 oct. 2014 17:32
Dernière modification :	30 oct. 2019 14:54

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