Automated Estimation of the Spinal Curvature via Spine Centerline Extraction with Ensembles of Cascaded Neural Networks

Florian Dubost, Benjamin Collery, Antonin Renaudier, Axel Roc, Nicolas Posocco, Wiro Niessen, Marleen de Bruijne

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

Scoliosis is a condition defined by an abnormal spinal curvature. For diagnosis and treatment planning of scoliosis, spinal curvature can be estimated using Cobb angles. We propose an automated method for the estimation of Cobb angles from X-ray scans. First, the centerline of the spine was segmented using a cascade of two convolutional neural networks. After smoothing the centerline, Cobb angles were automatically estimated using the derivative of the centerline. We evaluated the results using the mean absolute error and the average symmetric mean absolute percentage error between the manual assessment by experts and the automated predictions. For optimization, we used 609 X-ray scans from the London Health Sciences Center, and for evaluation, we participated in the international challenge “Accurate Automated Spinal Curvature Estimation, MICCAI 2019” (100 scans). On the challenge’s test set, we obtained an average symmetric mean absolute percentage error of 22.96.

Original languageEnglish
Title of host publicationComputational Methods and Clinical Applications for Spine Imaging - 6th International Workshop and Challenge, CSI 2019, Proceedings
EditorsYunliang Cai, Liansheng Wang, Michel Audette, Guoyan Zheng, Shuo Li
PublisherSpringer Open
Pages88-94
ISBN (Print)9783030397517
DOIs
Publication statusPublished - 2020
Event6th International Workshop and Challenge on Computational Methods and Clinical Applications for Spine Imaging, CSI 2019, held in conjunction with the 22nd International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2019 - Shenzhen, China
Duration: 17 Oct 201917 Oct 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11963 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Workshop and Challenge on Computational Methods and Clinical Applications for Spine Imaging, CSI 2019, held in conjunction with the 22nd International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2019
CountryChina
CityShenzhen
Period17/10/1917/10/19

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  • Cite this

    Dubost, F., Collery, B., Renaudier, A., Roc, A., Posocco, N., Niessen, W., & de Bruijne, M. (2020). Automated Estimation of the Spinal Curvature via Spine Centerline Extraction with Ensembles of Cascaded Neural Networks. In Y. Cai, L. Wang, M. Audette, G. Zheng, & S. Li (Eds.), Computational Methods and Clinical Applications for Spine Imaging - 6th International Workshop and Challenge, CSI 2019, Proceedings (pp. 88-94). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11963 LNCS). Springer Open. https://doi.org/10.1007/978-3-030-39752-4_10