Semi-automated estimation of spinal curvature from scoliosis radiographs using difference matrix

Rakshith Kamath, Anu Shaju Areeckal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Scoliosis is a medical condition in which there is a deformity and bending of the spine. Early detection and corrective measures can prevent severe cases, mainly in early childhood. The gold standard method for the diagnosis of scoliosis is the measurement of spine curvature using Cobb angle. In this paper, a semi-automated approach for accurate estimation of Cobb angles from scoliosis radiographs using a difference matrix is proposed. Given the landmark points of the vertebral columns in the spine, the spinal mid-line is determined by curve fitting of the 4th degree polynomial. Using a difference matrix created by calculating slopes in key points along the curve, Cobb angles are calculated. Data used in this work is obtained from the Accurate Automated Spinal Curvature Estimation (AASCE) Challenge 2019. The method is evaluated using mean absolute error and symmetric mean absolute percentage error. The proposed method gives promising results and could be used in accurate estimation of Cobb angle for the diagnosis of scoliosis.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages147-152
Number of pages6
ISBN (Electronic)9781728198859
DOIs
Publication statusPublished - 30-10-2020
Event2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Udupi, India
Duration: 30-10-202031-10-2020

Publication series

Name2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020 - Proceedings

Conference

Conference2020 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2020
Country/TerritoryIndia
CityUdupi
Period30-10-2031-10-20

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Electrical and Electronic Engineering
  • Control and Optimization
  • Artificial Intelligence
  • Computer Networks and Communications

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