The DOI matches its Crossref record; 56 of the 56 references it cites were found in a registry or an index.
Optimal Surface Segmentation in Volumetric Images-A Graph-Theoretic Approach
Open accessAbstract
Efficient segmentation of globally optimal surfaces representing object boundaries in volumetric data sets is important and challenging in many medical image analysis applications. We have developed an optimal surface detection method capable of simultaneously detecting multiple interacting surfaces, in which the optimality is controlled by the cost functions designed for individual surfaces and by several geometric constraints defining the surface smoothness and interrelations. The method solves the surface segmentation problem by transforming it into computing a minimum s-t cut in a derived arc-weighted directed graph. The proposed algorithm has a low-order polynomial time complexity and is computationally efficient. It has been extensively validated on more than 300 computer-synthetic volumetric images, 72 CT-scanned data sets of different-sized plexiglas tubes, and tens of medical images spanning various imaging modalities. In all cases, the approach yielded highly accurate results. Our approach can be readily extended to higher-dimensional image segmentation.
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Cites
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Image Processing, Analysis and Machine Vision
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Self-citationInteractive graph cuts for optimal boundary & region segmentation of objects in N-D images
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Cited by
Graph Cuts and Efficient N-D Image Segmentation
Boykov, Y., & Funka-Lea, G. (2006) · International Journal of Computer Vision · doi:10.1007/s11263-006-7934-5 · Cited by 1,910
Retinal Imaging and Image Analysis
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Self-citationRetinal layer segmentation of macular OCT images using boundary classification
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Computer-Aided Diagnosis Systems for Lung Cancer: Challenges and Methodologies
El-Baz, A., Beache, G. M., Gimel'farb, G., Suzuki, K., Okada, K., Elnakib, A., Soliman, A., & Abdollahi, B. (2013) · International Journal of Biomedical Imaging · doi:10.1155/2013/942353 · Cited by 277
Automatic Liver Segmentation Based on Shape Constraints and Deformable Graph Cut in CT Images
Li, G., Chen, X., Shi, F., Zhu, W., Tian, J., & Xiang, D. (2015) · IEEE Transactions on Image Processing · doi:10.1109/tip.2015.2481326 · Cited by 185
(2013) · Liverpool John Moores University · Cited by 133
Medical Image Segmentation: Methods and Software
Withey, D. J., & Koles, Z. J. (2007) · 2007 Joint Meeting of the 6th International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the International Conference on Functional Biomedical Imaging · doi:10.1109/nfsi-icfbi.2007.4387709 · Cited by 113
Structured layer surface segmentation for retina OCT using fully convolutional regression networks
He, Y., Carass, A., Liu, Y., Jedynak, B. M., Solomon, S. D., Saidha, S., Calabresi, P. A., & Prince, J. L. (2021) · Medical Image Analysis · doi:10.1016/j.media.2020.101856 · Cited by 104
Automatic Detection and Segmentation of Lymph Nodes From CT Data
Barbu, A., Suehling, M., Xu, X., Liu, D., Zhou, S. K., & Comaniciu, D. (2012) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2011.2168234 · Cited by 94
Interactive segmentation of image volumes with Live Surface
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Metadata
- Authors
- Li, K., Wu, X., Chen, D. Z., & Sonka, M.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2006-01
- Volume
- 28
- Issue
- 1
- Pages
- 119-134
- ISSN
- 0162-8828 (ISSN-L)
- 2160-9292
- OpenAlex
- W2164774194
- Cited by
- 664
- References
- 56
- FWCI
- 23.52
- Type
- journal article
- Language
- en
- Open access
- green
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