The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Label Fusion in Atlas-Based Segmentation Using a Selective and Iterative Method for Performance Level Estimation (SIMPLE)
Abstract
In a multi-atlas based segmentation procedure, propagated atlas segmentations must be combined in a label fusion process. Some current methods deal with this problem by using atlas selection to construct an atlas set either prior to or after registration. Other methods estimate the performance of propagated segmentations and use this performance as a weight in the label fusion process. This paper proposes a selective and iterative method for performance level estimation (SIMPLE), which combines both strategies in an iterative procedure. In subsequent iterations the method refines both the estimated performance and the set of selected atlases. For a dataset of 100 MR images of prostate cancer patients, we show that the results of SIMPLE are significantly better than those of several existing methods, including the STAPLE method and variants of weighted majority voting.
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Nonrigid registration using free-form deformations: application to breast mr images
Rueckert, D., Sonoda, L. I., Hayes, C., Hill, D. L. G., Leach, M. O., & Hawkes, D. J. (1999) · IEEE Transactions on Medical Imaging · doi:10.1109/42.796284 · Cited by 5,265
Elastix: a toolbox for intensity-based medical image registration
Klein, S., Staring, M., Murphy, K., Viergever, M. A., & Pluim, J. (2010) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2009.2035616 · Cited by 4,311
Self-citationWarfield, S. K., Zou, K. H., & Wells, W. M. (2004) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2004.828354 · Cited by 2,072
Generalized Overlap Measures for Evaluation and Validation in Medical Image Analysis
Crum, W. R., Camara, O., & Hill, D. L. G. (2006) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2006.880587 · Cited by 776
Cited by
Evaluation of prostate segmentation algorithms for mri: The promise12 challenge
Litjens, G., Toth, R., van de Ven, W., Hoeks, C., Kerkstra, S., van Ginneken, B., Vincent, G., Guillard, G., Birbeck, N., Zhang, J., et al. (2014) · Medical Image Analysis · doi:10.1016/j.media.2013.12.002 · Cited by 857
Multi-atlas segmentation of biomedical images: A survey
Iglesias, J. E., & Sabuncu, M. R. (2015) · Medical Image Analysis · doi:10.1016/j.media.2015.06.012 · Cited by 667
Federated learning enables big data for rare cancer boundary detection
Pati, S., Baid, U., Edwards, B., Sheller, M., Wang, S.-H., Reina, G. A., Foley, P., Gruzdev, A., Karkada, D., Davatzikos, C., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-33407-5 · Cited by 394
Pati, S., Baid, U., Edwards, B., Sheller, M. J., Foley, P., Anthony Reina, G., Thakur, S., Sako, C., Bilello, M., Davatzikos, C., et al. (2022) · Physics in Medicine & Biology · doi:10.1088/1361-6560/ac9449 · Cited by 51
Metadata
- Authors
- Langerak, T. R., van der Heide, U. A., Kotte, A. N. T. J., Viergever, M. A., van Vulpen, M., & Pluim, J. P. W.
- Venue
- IEEE Transactions on Medical Imaging
- Published
- 2010-12
- Volume
- 29
- Issue
- 12
- Pages
- 2000-2008
- ISSN
- 0278-0062 (ISSN-L)
- 1558-254X
- OpenAlex
- W2163595993
- Cited by
- 261
- References
- 4
- FWCI
- 19.53
- Type
- journal article
- Language
- en
- Open access
- closed
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- Langerak, T. R., van der Heide, U. A., Kotte, A. N. T. J., Viergever, M. A., van Vulpen, M., & Pluim, J. P. W. (2010). Label Fusion in Atlas-Based Segmentation Using a Selective and Iterative Method for Performance Level Estimation (SIMPLE). IEEE Transactions on Medical Imaging. https://doi.org/10.1109/tmi.2010.2057442
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