Abstract
This paper presents an algorithm for automatic segmentation of brain tissue from three dimensional (3-D) Magnetic Resonance (MR) images. The technique fuses morphological filtering by reconstruction (which analyzes the geometrical information), and histogram based thresholding (for gray level tissue classification). Segmentation is performed by watershed analysis of the 3-D data set. The algorithm effectively discriminates the brain tissue from the rest of the anatomical structures within the MR signal. The robustness of this technique has been successfully tested on numerous patient data sets.
We appreciate Dr. Tracy Faber for her thoughtful comments during the development of this project, and Dr. John Hoffman for providing the data sets. Dr. Faber is assistant professor, and Dr. Hoffman is associate professor, both with the Department of Radiology at Emory University (Atlanta, GA, USA).
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© 1996 Kluwer Academic Publishers
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Madrid, J., Ezquerra, N. (1996). Automatic 3-Dimensional Segmentation of MR Brain Tissue Using Filters by Reconstruction. In: Maragos, P., Schafer, R.W., Butt, M.A. (eds) Mathematical Morphology and its Applications to Image and Signal Processing. Computational Imaging and Vision, vol 5. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-0469-2_49
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DOI: https://doi.org/10.1007/978-1-4613-0469-2_49
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