Abstract
This paper describes an automatic system for intervertebral discs (IVDs) localization and segmentation in three-dimensional magnetic resonance imaging scans. The system builds upon the localization and segmentation system first introduced by Lootus et al. with several improvements to the localization step. The system was trained on T1 and T2 scans of 341 patients obtained from various sources. The proposed system achieved a mean localization error of \(1.1\,{\pm }\,0.6\) mm and a mean Dice overlap coefficient of \(84.0\,{\pm }\,1.5\,\%\) on the 15 training data of the challenge on IVD localization and segmentation at the 3rd MICCAI Workshop & Challenge on Computational Methods and Clinical Applications for Spine Imaging - MICCAI–CSI2015.
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Acknowledgements
We are grateful for discussions with Prof. Jeremy Fairbank, and Dr. Jill Urban. This work was supported by the RCUK CDT in Healthcare Innovation (EP/G036861/1). The data used in this research was obtained during the EC FP7 project HEALTH-F2-2008-201626.
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Jamaludin, A., Lootus, M., Kadir, T., Zisserman, A. (2016). Automatic Intervertebral Discs Localization and Segmentation: A Vertebral Approach. In: Vrtovec, T., et al. Computational Methods and Clinical Applications for Spine Imaging. CSI 2015. Lecture Notes in Computer Science(), vol 9402. Springer, Cham. https://doi.org/10.1007/978-3-319-41827-8_9
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DOI: https://doi.org/10.1007/978-3-319-41827-8_9
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