Abstract
This paper presents a new atlas-based segmentation framework for the delineation of major regions in magnetic resonance brain images employing an atlas of the global topological structure as well as a statistical atlas of the regions of interest. A segmentation technique using fast marching methods and tissue classification is proposed that guarantees strict topological equivalence between the segmented image and the atlas. Experimental validation on simulated and real brain images shows that the method is accurate and robust.
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Keywords
- Magnetic Resonance Brain Image
- Manual Segmentation
- Medical Image Computing
- Brain Segmentation
- Atlas Image
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Bazin, PL., Pham, D.L. (2007). Statistical and Topological Atlas Based Brain Image Segmentation. In: Ayache, N., Ourselin, S., Maeder, A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007. MICCAI 2007. Lecture Notes in Computer Science, vol 4791. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75757-3_12
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DOI: https://doi.org/10.1007/978-3-540-75757-3_12
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