Garcia Cano, Edgar, Arambula, Fernando, Duong, Luc, Bellefleur, Christian, Roy Beaudry, Marjolaine, Joncas, Julien and Parent, Stephan.
19 November 2018.
« Dynamic Classification of Abnormal Spinal Curves ».
[Research article]. Substance ÉTS.
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: | https://espace2.etsmtl.ca/id/eprint/18316 |
Actions (login required)
View Item |