The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain
Abstract
Magnetic resonance (MR) brain section images are segmented and then synthetically colored to give visual representations of the original data with three approaches: the literal and approximate fuzzy c-means unsupervised clustering algorithms, and a supervised computational neural network. Initial clinical results are presented on normal volunteers and selected patients with brain tumors surrounded by edema. Supervised and unsupervised segmentation techniques provide broadly similar results. Unsupervised fuzzy algorithms were visually observed to show better segmentation when compared with raw image data for volunteer studies. For a more complex segmentation problem with tumor/edema or cerebrospinal fluid boundary, where the tissues have similar MR relaxation behavior, inconsistency in rating among experts was observed, with fuzz-c-means approaches being slightly preferred over feedforward cascade correlation results. Various facets of both approaches, such as supervised versus unsupervised learning, time complexity, and utility for the diagnostic process, are compared.
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Cited by
Statistical approach to segmentation of single-channel cerebral MR images
Rajapakse, J. C., Giedd, J. N., & Rapoport, J. L. (1997) · IEEE Transactions on Medical Imaging · doi:10.1109/42.563663 · Cited by 678
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An adaptive spatial fuzzy clustering algorithm for 3-D MR image segmentation
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Unstructured data in marketing
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Normal brain volume measurements using multispectral MRI segmentation
Vaidyanathan, M., Clarke, L. P., Heidtman, C., Velthuizen, R. P., & Hall, L. O. (1997) · Magnetic Resonance Imaging · doi:10.1016/s0730-725x(96)00244-5 · Cited by 39
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Metadata
- Authors
- Hall, L. O., Bensaid, A. M., Clarke, L. P., Velthuizen, R. P., Silbiger, M. S., & Bezdek, J. C.
- Venue
- IEEE Transactions on Neural Networks
- Published
- 1992
- Volume
- 3
- Issue
- 5
- Pages
- 672-682
- ISSN
- 1045-9227 (ISSN-L)
- OpenAlex
- W2108843657
- Cited by
- 580
- References
- 23
- FWCI
- 17.02
- Type
- journal article
- Language
- en
- Open access
- closed
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