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Published in:
Detection of Sclerotic Spine Metastases via Random Aggregation of Deep Convolutional Neural Network Classifications Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Report of Vertebra Segmentation Challenge in 2014 MICCAI Workshop on Computational Spine Imaging

Authors : Jianhua Yao, Shuo Li

Published in: Recent Advances in Computational Methods and Clinical Applications for Spine Imaging

Publisher: Springer International Publishing

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Abstract

Segmentation is the fundamental step for most spine image analysis tasks. The vertebra segmentation challenge held at the 2014 Computational Spine Imaging Workshop (CSI2014) objectively evaluated the performance of several algorithms segmenting vertebrae in spine CT scans. Five teams participated in the challenge. Ten training data sets and Five test data sets with reference annotation were provided for training and evaluation. Dice coefficient and absolute surface distances were used as the evaluation metrics. The segmentations on both the whole vertebra and its substructures were evaluated. The performances comparisons were assessed in different aspects. The top performers in the challenge achieved Dice coefficient of 0.93 in the upper thoracic, 0.95 in the lower thoracic and 0.96 in the lumbar spine. The strength and weakness of each method are discussed in this paper.

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previous chapter 3D Vertebra Segmentation by Feature Selection Active Shape Model
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Metadata
Title
Report of Vertebra Segmentation Challenge in 2014 MICCAI Workshop on Computational Spine Imaging
Authors
Jianhua Yao
Shuo Li
Copyright Year
2015
Book
Recent Advances in Computational Methods and Clinical Applications for Spine Imaging

Print ISBN: 978-3-319-14147-3

Electronic ISBN: 978-3-319-14148-0

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-14148-0_23