FRANÇAIS
A showcase of ÉTS researchers’ publications and other contributions
SEARCH

Dynamic Classification of Abnormal Spinal Curves

Downloads

Downloads per month over past year

Garcia Cano, Edgar, Arambula, Fernando, Duong, Luc, Bellefleur, Christian, Roy Beaudry, Marjolaine, Joncas, Julien et Parent, Stephan. 19 November 2018. « Dynamic Classification of Abnormal Spinal Curves ». [Research article]. Substance ÉTS.

[img]
Preview
PDF
Substance 2018 18316 Dynamic Classification of Abnormal.pdf - Published Version
Use licence: Creative Commons CC BY-NC.

Download (2MB) | Preview

Abstract

Adolescent Idiopathic Scoliosis (AIS) is a 3D deformation of the spine. AIS usually affects the younger population in the early stages of puberty and is more frequent in females than in males. As in any other medical condition, assessment is an important step to provide adequate treatment and follow-up for each patient. The Lenke classification is the common criterion used by clinicians to categorize spinal curvatures based on 2D measurements. These are obtained from radiographs of the spine in a standing position. The goal of this study is to classify scoliotic curves. We propose a technique called leave-n-out angle to describe spines from 3D reconstructions, and a Dynamic Ensemble Selection (DES), a Machine Learning method to automatically assess curvature types. Keywords: spine classification, descriptors of the spine, Adolescent Idiopathic Scoliosis, Dynamic Ensemble Selection, machine learning

Item Type: Non-peer reviewed article published in a journal or magazine
Refereed: No
Professor:
Professor
Duong, Luc
Affiliation: Génie logiciel et des technologies de l'information
Date Deposited: 26 Mar 2019 16:09
Last Modified: 02 Apr 2019 14:52
URI: http://espace2.etsmtl.ca/id/eprint/18316

Actions (login required)

View Item View Item