Abstract
The preprocessing of 3-dimensional (3D) MRI data constitutes a bottleneck in the process of visualizing the brain surface with volume rendering. As a fast way to achieve this preprocessing, the authors propose a simple pipeline based on an algorithm of seedgrowing type, for approximate segmentation of the intradural space in T1-weighted 3D MRI data. Except for the setting of a seed and four parameters, this pipeline proceeds in an unsupervised manner; no interactive intermediate step is involved. It was tested with 15 datasets from normal adults. The result was reproducible in that as long as the seed was located within the cerebral white matter, identical segmentation was achieved for each dataset. Although the pipeline ran with gross segmentation error along the floor of the cranial cavity, it performed well along the cranial vault so that subsequent volume rendering permitted the observation of the sulco-gyral pattern over cerebral convexities. Use of this pipeline followed by volume rendering is a handy approach to the visualization of the brain surface from 3D MRI data.
Key Words: magnetic resonance imaging, segmentation, intradural space, volume rendering, visualization, brain surface
Full Text
The Full Text of this article is available as a PDF (1.8 MB).
References
- 1.Frenkel KA. Volume rendering. Comm ACM. 1989;32:426–435. doi: 10.1145/63334.63335. [DOI] [Google Scholar]
- 2.Levin DN, Hu X, Tan KK, et al. Surface of the brain: Three-dimensional MR images created with volume rendering. Radiology. 1989;171:277–280. doi: 10.1148/radiology.171.1.2928539. [DOI] [PubMed] [Google Scholar]
- 3.Bezdek JC, Hall LO, Clarke LP. Review of MR image segmentation techniques using pattern recognition. Med Phys. 1993;20:1033–1048. doi: 10.1118/1.597000. [DOI] [PubMed] [Google Scholar]
- 4.Joliot M, Mazoyer BM. Three-dimensional segmentation and interpolation of magnetic resonance brain images. IEEE Trans Med Imaging. 1993;12:269–277. doi: 10.1109/42.232255. [DOI] [PubMed] [Google Scholar]
- 5.Filipek PA, Kennedy DN, Caviness VS, et al. Magnetic resonance imaging-based brain morphometry: Development and application to normal subjects. Ann Neurol. 1989;25:61–67. doi: 10.1002/ana.410250110. [DOI] [PubMed] [Google Scholar]
- 6.Bomans M, Höhne KH, Tiede U, et al. 3-D segmentation of MR images of the head for 3-D display. IEEE Trans Med Imaging. 1990;9:177–183. doi: 10.1109/42.56342. [DOI] [PubMed] [Google Scholar]
- 7.Cline HE, Dumoulin CL, Hart HR, et al. 3D reconstruction of the brain from magnetic resonance images using a connectivity algorithm. Magn Reson Imaging. 1987;5:345–352. doi: 10.1016/0730-725X(87)90124-X. [DOI] [PubMed] [Google Scholar]
- 8.Brummer ME, Mersereau RM, Eisner RL, et al. Automatic detection of brain contours in MRI data sets. IEEE Trans Med Imaging. 1993;12:153–166. doi: 10.1109/42.232244. [DOI] [PubMed] [Google Scholar]
- 9.Snell JW, Merickel MB, Ortega JM, et al. Model-based boundary estimation of complex objects using hierarchical active surface templates. Pattern Recognition. 1995;28:1599–1609. doi: 10.1016/0031-3203(95)00021-Q. [DOI] [Google Scholar]
- 10.Toh MY, Falk RB, Main JS. Interactive brain atlas with the visible human project data: Development methods and techniques. Radiographics. 1996;16:1201–1206. doi: 10.1148/radiographics.16.5.8888399. [DOI] [PubMed] [Google Scholar]
- 11.Gerig G, Kübler O, Kikinis R, et al. Nonlinear anisotropic filtering of MRI data. IEEE Trans Med Imaging. 1992;11:221–232. doi: 10.1109/42.141646. [DOI] [PubMed] [Google Scholar]
- 12.Kaufman L, Kramer DM, Crooks LE, et al. Measuring signal-to-noise ratios in MR imaging. Radiology. 1989;173:265–267. doi: 10.1148/radiology.173.1.2781018. [DOI] [PubMed] [Google Scholar]
- 13.Clarke LP, Velthuizen RP, Camacho MA, et al. MRI segmentation: Methods and applications. Magn Reson Imaging. 1995;13:343–368. doi: 10.1016/0730-725X(94)00124-L. [DOI] [PubMed] [Google Scholar]
- 14.Kikinis R, Shenton ME, Gerig G, et al. Temporal lobe sulco-gyral pattern anomalies in schizophrenia: an in vivo MR three-dimensional surface rendering study. Neurosci Lett. 1994;182:7–12. doi: 10.1016/0304-3940(94)90192-9. [DOI] [PubMed] [Google Scholar]
- 15.Sisodiya SM, Stevens JM, Fish DR, et al. The demonstration of gyral abnormalities in patients with cryptogenic partial epilepsy using three-dimensional MRI. Arch Neurol. 1996;53:28–34. doi: 10.1001/archneur.1996.00550010038014. [DOI] [PubMed] [Google Scholar]
- 16.Bartley AJ, Jones DW, Weinberger DR. Genetic variability of human brain size and cortical gyral patterns. Brain. 1997;120:257–269. doi: 10.1093/brain/120.2.257. [DOI] [PubMed] [Google Scholar]
- 17.Biondi A, Nogueira H, Dormont D, et al. Are the brains of monozygotic twins similar? A three-dimensional MR study. Am J Neuroradiol. 1998;19:1361–1367. [PMC free article] [PubMed] [Google Scholar]