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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, & De Guise, Jacques A. (2010). A computer-aided method for scoliosis fusion level selection by a topologically ordered self organizing Kohonen network. In 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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  PDF - ICPR2010NMezghani.pdf
Content : Accepted Version
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Item Type: Papers in Conference Proceedings
Refereed: Yes
Status: Published
Abstract: 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.
Official URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arn...
Depositor: Mezghani, Neila
Owner / Manager: Neila Mezghani
Deposited: 24 Oct 2014 17:32
Last Modified: 16 Jul 2015 00:46

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