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Dynamic ensemble selection of learner-descriptor classifiers to assess curve types in adolescent idiopathic scoliosis

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Abstract

While classification is important for assessing adolescent idiopathic scoliosis (AIS), it however suffers from low interobserver and intraobserver reliability. Classification using ensemble methods may contribute to improving reliability using the proper 2D and 3D images of spine curvature features. In this study, we present two new techniques to describe the spine, namely, leave-one-out and fan leave-one-out. Using these techniques, three descriptors are computed from a stereoradiographic 3D reconstruction to describe the relationship between a vertebra and its neighbors. A dynamic ensemble selection method is introduced for automatic spine classification. The performance of the method is evaluated on a dataset containing 962 3D spine models categorized according to three curve types. With a log loss of 0.5623, the dynamic ensemble selection outperforms voting and stacking ensemble learning techniques. This method can improve intraobserver and interobserver reliability, identify the best combination of descriptors for characterizing spine curve types, and provide assistance to clinicians in the form of information to classify borderline curvature types.

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Acknowledgments

A preliminary short abstract of this work was presented in [10].

Funding

This research was funded by CONACYT CVU 323619 in Mexico, Fonds de recherche du Québec – Nature et technologies (FRQNT), file 194703, and the Ministère des Relations internationales et de la Francophonie.

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Authors and Affiliations

  1. École de technologie supérieure, 1100 Notre-Dame Street West, Montreal, Quebec, H3C 1K3, Canada

    Edgar García-Cano & Luc Duong

  2. Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Circuito Escolar S/N. Ciudad Universitaria, C.P. 04510, Mexico, D.F., Mexico

    Fernando Arámbula Cosío

  3. Research Center, Sainte-Justine Hospital, 3175 Côte-Sainte-Catherine, Montreal, Quebec, Canada

    Christian Bellefleur, Marjolaine Roy-Beaudry, Julie Joncas, Stefan Parent & Hubert Labelle

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  1. Edgar García-Cano
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  3. Luc Duong
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  7. Stefan Parent
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  8. Hubert Labelle
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Correspondence to Edgar García-Cano.

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García-Cano, E., Arámbula Cosío, F., Duong, L. et al. Dynamic ensemble selection of learner-descriptor classifiers to assess curve types in adolescent idiopathic scoliosis. Med Biol Eng Comput 56, 2221–2231 (2018). https://doi.org/10.1007/s11517-018-1853-9

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  • DOI: https://doi.org/10.1007/s11517-018-1853-9

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