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International Workshop and Challenge on Computational Methods and Clinical Applications for Spine Imaging

CSI 2019: Computational Methods and Clinical Applications for Spine Imaging pp 81–87Cite as

Automatic Cobb Angle Detection Using Vertebra Detector and Vertebra Corners Regression

Part of the Lecture Notes in Computer Science book series (LNIP,volume 11963)

Abstract

Correct evaluation and treatment of Scoliosis require accurate estimation of spinal curvature. Current gold standard is to manually estimate Cobb Angles in spinal X-ray images which is time consuming and has high inter-rater variability. We propose an automatic method with a novel framework that first detects vertebrae as objects followed by a landmark detector that estimates the 4 landmark corners of each vertebra separately. Cobb Angles are calculated using the slope of each vertebra obtained from the predicted landmarks. For inference on test data, we perform pre and post processings that include cropping, outlier rejection and smoothing of the predicted landmarks. The results were assessed in AASCE MICCAI challenge 2019 which showed a promise with a SMAPE score of 25.69 on the challenge test set.

Keywords

  • Scoliosis
  • Landmark
  • Object detection
  • Cobb angle

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Fig. 1.
Fig. 2.

Notes

  1. 1.

    https://aasce19.grand-challenge.org/Home/.

  2. 2.

    http://spineweb.digitalimaginggroup.ca/spineweb/index.php?n=Main.Datasets.

  3. 3.

    http://spineweb.digitalimaginggroup.ca/spineweb/index.php?n=Main.Datasets.

  4. 4.

    https://github.com/tensorflow/models/tree/master/research/slim.

  5. 5.

    https://github.com/tryolabs/luminoth.

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Acknowledgements

This work is supported by NVIDIA GPU donation. We also thank Pro-Mech Minds & Engineering Services for agreeing to partially fund conference visit expenses for presenting this work.

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Authors and Affiliations

  1. NepAl Applied Mathematics and Informatics Institute for Research (NAAMII), Suryabinayak, Nepal

    Bidur Khanal, Lavsen Dahal & Bishesh Khanal

  2. Hospital for Advanced Medical Surgery (HAMS), Kathmandu, Nepal

    Prashant Adhikari

Authors
  1. Bidur Khanal
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  2. Lavsen Dahal
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  3. Prashant Adhikari
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  4. Bishesh Khanal
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Corresponding author

Correspondence to Bidur Khanal .

Editor information

Editors and Affiliations

  1. Worcester Polytechnic Institute, Worcester, MA, USA

    Yunliang Cai

  2. Xiamen University, Xiamen, China

    Liansheng Wang

  3. Old Dominion University, Norfolk, VA, USA

    Michel Audette

  4. Shanghai Jiao Tong University, Shanghai, China

    Guoyan Zheng

  5. Western University, London, ON, Canada

    Shuo Li

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Khanal, B., Dahal, L., Adhikari, P., Khanal, B. (2020). Automatic Cobb Angle Detection Using Vertebra Detector and Vertebra Corners Regression. In: Cai, Y., Wang, L., Audette, M., Zheng, G., Li, S. (eds) Computational Methods and Clinical Applications for Spine Imaging. CSI 2019. Lecture Notes in Computer Science(), vol 11963. Springer, Cham. https://doi.org/10.1007/978-3-030-39752-4_9

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  • DOI: https://doi.org/10.1007/978-3-030-39752-4_9

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