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We present tree extraction in 3D images as a graph refinement task, of obtaining a subgraph from an over-complete input graph.
Jaakkola, Tommi S., Michael I. Jordan. ”Improving the mean field approximation via the use of mixture distributions.” Learning in graphical models. Springer(1998)
1998
Earlier work this paper cites.
Zhang, Yongyue, Michael Brady, and Stephen Smith. ”Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm.” IEEE transactions on medical imaging 20.1 (2001): 45-57
2001
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Wang, XiaoFeng, and Xiao-Ping Zhang. ”A new localized superpixel Markov random field for image segmentation.” Multimedia and Expo, 2009. ICME 2009. IEEE International Conference on. IEEE, 2009
2009
Earlier work this paper cites.
Lo, Pechin, et al. ”Airway tree extraction with locally optimal paths.” International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Berlin, Heidelberg, 2009
2009
Earlier work this paper cites.
Pedersen, Jesper H., et al. ”The Danish randomized lung cancer CT screening trial—overall design and results of the prevalence round.” Journal of Thoracic Oncology 4.5 (2009): 608-614
2009
Cited alongside, same era.
Lo, Pechin, et al. ”Vessel-guided airway tree segmentation: A voxel classification approach.” Medical image analysis 14.4 (2010): 527-538
2010
Cited alongside, same era.
2014
Cited alongside, same era.
Li, Yujia, and Richard Zemel. ”Mean-Field Networks.” arXiv preprint arXiv:1410.5884 (2014)
2014
Cited alongside, same era.
Orlando, José Ignacio, and Matthew Blaschko. ”Learning fully-connected CRFs for blood vessel segmentation in retinal images.” International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Cham, 2014
2014
Later among the works it cites.
2017
Later among the works it cites.
Lo, Pechin, et al. ”Extraction of airways from CT (EXACT’09).” IEEE Transactions on Medical Imaging 31.11 (2012): 2093-2107
2093
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