TY - JFULL AU - Neila Mezghani and Philippe Phan and Hubert Labelle and Carl Eric Aubin and Jacques de Guise PY - 2009/6/ TI - Computer-aided Lenke Classification of Scoliotic Spines T2 - International Journal of Computer and Information Engineering SP - 1350 EP - 1354 VL - 3 SN - 1307-6892 UR - https://publications.waset.org/pdf/3958 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 29, 2009 N2 - The identification and classification of the spine deformity play an important role when considering surgical planning for adolescent patients with idiopathic scoliosis. The subject of this article is the Lenke classification of scoliotic spines using Cobb angle measurements. The purpose is two-fold: (1) design a rulebased diagram to assist clinicians in the classification process and (2) investigate a computer classifier which improves the classification time and accuracy. The rule-based diagram efficiency was evaluated in a series of scoliotic classifications by 10 clinicians. The computer classifier was tested on a radiographic measurement database of 603 patients. Classification accuracy was 93% using the rule-based diagram and 99% for the computer classifier. Both the computer classifier and the rule based diagram can efficiently assist clinicians in their Lenke classification of spine scoliosis. ER -