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    Brain MRI T₁-Map and T₁-weighted Image Segmentation in a Variational Framework

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    icassp_Brain_MRI_T1-Map.pdf (355.3Kb)
    Date
    2009-06
    Author
    Cheng, Ping-Feng
    Steen, R.Grant
    Yezzi, Anthony
    Krim, Hamid
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    Abstract
    In this paper we propose a constrained version of Mumford- Shah’s[1] segmentationwith an information-theoretic point of view[2] in order to devise a systematic procedure to segment brain MRI data for two modalities of parametric T₁-Map and T₁-weighted images in both 2-D and 3-D settings. The incorporation of a tuning weight in particular adds a probabilistic flavor to our segmentation method, and makes the three-tissue segmentation possible. Our method uses region based active contours which have proven to be robust. The method is validated by two real objects which were used to generate T₁- Maps and also by two simulated brains of T₁-weighted data from the BrainWeb[3] public database.
    URI
    http://hdl.handle.net/1853/48951
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    • Laboratory of Computational Computer Vision Publications [106]

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