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Evaluation and Comparison of Automatic Intervertebral Disc Localization and Segmentation methods with 3D Multi-modality MR Images: A Grand Challenge

  • Guodong ZengEmail author
  • Daniel Belavy
  • Shuo Li
  • Guoyan Zheng
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11397)

Abstract

The localization and segmentation of Intervertebral Discs (IVDs) with 3D Multi-modality MR Images are critically important for spine disease diagnosis and measurements. Manual annotation is a tedious and laborious procedure. There exist automatic IVD localization and segmentation methods on multi-modality IVD MR images, but an objective comparison of such methods is lacking. Thus we organized the following challenge: Automatic Intervertebral Disc Localization and Segmentation from 3D Multi-modality MR Images, held at the 2018 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2018). Our challenge ensures an objective comparison by running 8 submitted methods with docker container. Experimental results show that overall the best localization method achieves a mean localization distance of 0.77 mm and the best segmentation method achieves a mean Dice of 90.64% and a mean average absolute distance of 0.60 mm, respectively. This challenge still keeps open for future submission and provides an online platform for methods comparison.

Keywords

Intervertebral disc MRI Localization Segmentation Multi-modality Challenge 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Guodong Zeng
    • 1
    Email author
  • Daniel Belavy
    • 2
  • Shuo Li
    • 3
  • Guoyan Zheng
    • 1
  1. 1.Institute for Surgical Technology and BiomechanicsUniversity of BernBernSwitzerland
  2. 2.Deakin UniversityGeelongAustralia
  3. 3.University of Western OntarioLondonCanada

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