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Automatic detection of brain contours in MRI data sets
Abstract
A software procedure is presented for fully automated detection of brain contours from single-echo 3-D MRI data, developed initially for scans with coronal orientation. The procedure detects structures in a head data volume in a hierarchical fashion. Automatic detection starts with a histogram-based thresholding step, whenever necessary preceded by an image intensity correction procedure. This step is followed by a morphological procedure which refines the binary threshold mask images. Anatomical knowledge, essential for the discrimination between desired and undesired structures, is implemented in this step through a sequence of conventional and novel morphological operations, using 2-D and 3-D operations. A final step of the procedure performs overlap tests on candidate brain regions of interest in neighboring slice images to propagate coherent 2-D brain masks through the third dimension. Results are presented for test runs of the procedure on 23 coronal whole-brain data sets, and one sagittal whole-brain data set. Finally, the potential of the technique for generalization to other problems is discussed, as well as limitations of the technique.
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Citations
Cites
A Computational Approach to Edge Detection
Canny, J. (1986) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1986.4767851 · Cited by 30,004
Cited by
Fast robust automated brain extraction
Smith, S. M. (2002) · Human Brain Mapping · doi:10.1002/hbm.10062 · Cited by 10,496
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
Soler, L., Delingette, H., Malandain, G., Montagnat, J., Ayache, N., Koehl, C., Dourthe, O., Malassagne, B., Smith, M., Mutter, D., et al. (2001) · Computer Aided Surgery · doi:10.1002/igs.1016 · Cited by 320
An adaptive spatial fuzzy clustering algorithm for 3-D MR image segmentation
Liew, A. W.-C., & Yan, H. (2003) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2003.816956 · Cited by 316
ANIMAL+INSECT: Improved Cortical Structure Segmentation
Collins, D. L., Zijdenbos, A. P., Baaré, W. F. C., & Evans, A. C. (1999) · Lecture Notes in Computer Science · doi:10.1007/3-540-48714-x_16 · Cited by 253
Metadata
- Authors
- Brummer, M. E., Mersereau, R. M., Eisner, R. L., & Lewine, R. R. J.
- Venue
- IEEE Transactions on Medical Imaging
- Published
- 1993-06
- Volume
- 12
- Issue
- 2
- Pages
- 153-166
- ISSN
- 0278-0062 (ISSN-L)
- OpenAlex
- W2132499268
- Cited by
- 297
- References
- 1
- FWCI
- 16.67
- Type
- journal article
- Language
- en
- Open access
- closed
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- Brummer, M. E., Mersereau, R. M., Eisner, R. L., & Lewine, R. R. J. (1993). Automatic detection of brain contours in MRI data sets. IEEE Transactions on Medical Imaging. https://doi.org/10.1109/42.232244
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