Abstract
This paper presents one of the participating methods to the intervertebral disc segmentation challenge organized in conjunction with the 3rd MICCAI Workshop & Challenge on Computational Methods and Clinical Applications for Spine Imaging - MICCAI–CSI2015. The presented method consist of three steps. In the first step, vertebral bodies are detected and labeled using integral channel features and a graphical parts model. The second step consists of image registration, where a set of image volumes with corresponding intervertebral disc atlases are registered to the target volume using the output from the first step as initialization. In the final step, the registered atlases are combined using label fusion to derive the final segmentation. The pipeline was evaluated using a set of \(15+10\) T2-weighted image volumes provided as training and test data respectively for the segmentation challenge. For the training data, a mean disc centroid distance of 0.86 mm and an average DICE score of 91 % was achieved, and for the test data the corresponding results were 0.90 mm and 90 %.
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Acknowledgements
The work of D.F. was partially funded by the Swedish Innovation Agency (VINNOVA), grant 2014-01422.
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Wang, C., Forsberg, D. (2016). Segmentation of Intervertebral Discs in 3D MRI Data Using Multi-atlas Based Registration. 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_10
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DOI: https://doi.org/10.1007/978-3-319-41827-8_10
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