This paper studies dynamic contrast-enhanced magnetic resonance imaging, a technique to estimate maps of physiological parameters describing tissue perfusion at the capillary level. One of the most challenging problems of this imaging method is the measurement of the arterial input function. One possibility to estimate the arterial input function is based on multi-channel blind deconvolution applied to signals measured in several tissue regions. An extension to the published methods is presented. A new regularization term is introduced and a more complex model of the tissue residual function is used. Tests on synthetic and clinical data demonstrate the reliability of the method.
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Mem Sloan Kettering Canc Ctr, Dept Med Phys, New York, NY 10021 USAMem Sloan Kettering Canc Ctr, Dept Med Phys, New York, NY 10021 USA
Wang, Ya
Huang, Wei
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Mem Sloan Kettering Canc Ctr, Dept Med Phys, New York, NY 10021 USA
Cornell Univ, Weill Med Coll, Dept Radiol, New York, NY 10021 USAMem Sloan Kettering Canc Ctr, Dept Med Phys, New York, NY 10021 USA
Huang, Wei
Panicek, David A.
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Mem Sloan Kettering Canc Ctr, Dept Radiol, New York, NY 10021 USA
Cornell Univ, Weill Med Coll, Dept Radiol, New York, NY 10021 USAMem Sloan Kettering Canc Ctr, Dept Med Phys, New York, NY 10021 USA
Panicek, David A.
Schwartz, Lawrence H.
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Mem Sloan Kettering Canc Ctr, Dept Radiol, New York, NY 10021 USA
Cornell Univ, Weill Med Coll, Dept Radiol, New York, NY 10021 USAMem Sloan Kettering Canc Ctr, Dept Med Phys, New York, NY 10021 USA
Schwartz, Lawrence H.
Koutcher, Jason A.
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Mem Sloan Kettering Canc Ctr, Dept Med Phys, New York, NY 10021 USA
Mem Sloan Kettering Canc Ctr, Dept Med, New York, NY 10021 USAMem Sloan Kettering Canc Ctr, Dept Med Phys, New York, NY 10021 USA