Abstract
A new physically justified adaptive probabilistic model of blood vessels on magnetic resonance angiography (MRA) images is proposed. The model accounts for both laminar (for normal subjects) and turbulent blood flow (in abnormal cases like anemia or stenosis) and results in a fast algorithm for extracting a 3D cerebrovascular system from the MRA data. Experiments with synthetic and 50 real data sets confirm the high accuracy of the proposed approach.
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El-Baz, A., Farag, A.A., Gimel’farb, G., El-Ghar, M.A., Eldiasty, T. (2006). A New Adaptive Probabilistic Model of Blood Vessels for Segmenting MRA Images. In: Larsen, R., Nielsen, M., Sporring, J. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006. MICCAI 2006. Lecture Notes in Computer Science, vol 4191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11866763_98
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DOI: https://doi.org/10.1007/11866763_98
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