The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Current Methods in Medical Image Segmentation
Abstract
▪ Abstract Image segmentation plays a crucial role in many medical-imaging applications, by automating or facilitating the delineation of anatomical structures and other regions of interest. We present a critical appraisal of the current status of semiautomated and automated methods for the segmentation of anatomical medical images. Terminology and important issues in image segmentation are first presented. Current segmentation approaches are then reviewed with an emphasis on the advantages and disadvantages of these methods for medical imaging applications. We conclude with a discussion on the future of image segmentation methods in biomedical research.
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Cites
A nonparametric method for automatic correction of intensity nonuniformity in MRI data
Sled, J. G., Zijdenbos, A. P., & Evans, A. C. (1998) · IEEE Transactions on Medical Imaging · doi:10.1109/42.668698 · Cited by 4,731
Snakes, shapes, and gradient vector flow
Xu, C., & Prince, J. L. (1998) · IEEE Transactions on Image Processing · doi:10.1109/83.661186 · Cited by 4,001
Self-citation
Cited by
Artificial intelligence in radiology
Hosny, A., Parmar, C., Quackenbush, J., Schwartz, L. H., & Aerts, H. J. W. L. (2018) · Nature Reviews Cancer · doi:10.1038/s41568-018-0016-5 · Cited by 3,803
Brain development in children and adolescents: Insights from anatomical magnetic resonance imaging
Lenroot, R. K., & Giedd, J. N. (2006) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2006.06.001 · Cited by 1,863
A survey of MRI-based medical image analysis for brain tumor studies
Bauer, S., Wiest, R., Nolte, L.-P., & Reyes, M. (2013) · Physics in Medicine and Biology · doi:10.1088/0031-9155/58/13/r97 · Cited by 1,036
Geometrically Accurate Topology-Correction of Cortical Surfaces Using Nonseparating Loops
Segonne, F., Pacheco, J., & Fischl, B. (2007) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2006.887364 · Cited by 992
Segment anything model for medical image analysis: An experimental study
Mazurowski, M. A., Dong, H., Gu, H., Yang, J., Konz, N., & Zhang, Y. (2023) · Medical Image Analysis · doi:10.1016/j.media.2023.102918 · Cited by 802
“Image segmentation is a central task in medical image analysis, ranging from the segmentation of organs [17], abnormalities [3], bones [8], and others [13].”
Background
Metadata
- Authors
- Pham, D. L., Xu, C., & Prince, J. L.
- Venue
- Annual Review of Biomedical Engineering
- Publisher
- Annual Reviews
- Published
- 2000-08
- Volume
- 2
- Issue
- 1
- Pages
- 315-337
- ISSN
- 1523-9829 (ISSN-L)
- 1545-4274
- OpenAlex
- W2118386984
- Cited by
- 2,341
- References
- 2
- FWCI
- 2.29
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Current Methods in Medical Image Segmentation. https://app.cochat.ai/papers/10.1146/annurev.bioeng.2.1.315
- The paper
- Pham, D. L., Xu, C., & Prince, J. L. (2000). Current Methods in Medical Image Segmentation. Annual Review of Biomedical Engineering. https://doi.org/10.1146/annurev.bioeng.2.1.315
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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