Abstract
We describe a combination of a region growing and a watershed algorithm optimized for the detection of homogeneous structures in magnetic resonance (MR) volume datasets. No prior knowledge is used except a segment model. The adaptation to different data sets is controlled by parameters which can be determined interactively due to the high speed of the algorithm. Results are shown for the segmentation of the basal ganglia and the white matter of the brain.
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© 1995 Springer-Verlag Berlin Heidelberg
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Mittelhäußer, G., Kruggel, F. (1995). Fast Segmentation of Brain Magnetic Resonance Tomograms. In: Ayache, N. (eds) Computer Vision, Virtual Reality and Robotics in Medicine. CVRMed 1995. Lecture Notes in Computer Science, vol 905. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-49197-2_27
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DOI: https://doi.org/10.1007/978-3-540-49197-2_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-59120-7
Online ISBN: 978-3-540-49197-2
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