Automatic assessment of skeletal maturity in adolescent idiopathic scoliosis patients using support vector regression on deep features

Hilary Cintia Djuikoua Wouafo; Julie Joncas; Marjolaine Roy-Beaudry; Soraya Barchi; Stefan Parent; Hubert Labelle; Luc Duong

doi:10.1117/12.2653393

3 April 2023 Automatic assessment of skeletal maturity in adolescent idiopathic scoliosis patients using support vector regression on deep features

Hilary Cintia Djuikoua Wouafo, Julie Joncas, Marjolaine Roy-Beaudry, Soraya Barchi, Stefan Parent, Hubert Labelle, Luc Duong

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Proceedings Volume 12467, Medical Imaging 2023: Image Perception, Observer Performance, and Technology Assessment; 1246711 (2023) https://doi.org/10.1117/12.2653393
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

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Abstract

Skeletal maturity assessment is an important step in the treatment of adolescent idiopathic scoliosis (AIS). Traditional methods rely on the bone age assessment using 2D X-ray radiography. Assessment is generally performed using the Risser stages that is routinely used to assess the skeletal maturity through the observation of the level of ossification of iliac crests. This bone maturity assessment method is preferred in AIS but in practice, shows a rather high-level interobserver variability. This study aims to use an automatic Risser stage classification for a longitudinal study of follow-up visits to observe growth indicators of AIS patients. A regression model will then be used to evaluate the maturity changes of patients from à Risser stage to another. For the classification task, the pre-trained model of VGG16 was implemented with Python 3.10. The network parameters were changed since the task we were training it for contained a smaller dataset. The first experiments of this work were for the classification of the patient’s Risser signs. After several tests of optimization of the SVR classifiers hyperparameter, a mean square error of 0.38, a mean absolute error of 0.31 and an R² of 0.33. An optimization of the network and a pre-processing of the images will be done in the next phases of this project.

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Hilary Cintia Djuikoua Wouafo, Julie Joncas, Marjolaine Roy-Beaudry, Soraya Barchi, Stefan Parent, Hubert Labelle, and Luc Duong "Automatic assessment of skeletal maturity in adolescent idiopathic scoliosis patients using support vector regression on deep features", Proc. SPIE 12467, Medical Imaging 2023: Image Perception, Observer Performance, and Technology Assessment, 1246711 (3 April 2023); https://doi.org/10.1117/12.2653393

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