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ISSN infoPrint: 0040-585X
Electronic: 1095-7219
Coden: TPRBAU
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A Global Optimal Convergence Rate in a Model for the Diffusion Tensor Imaging
In their recent work Koltchinskii, Sakhanenko, and Cai [Ann. Statist., 35 (2007), pp. 1576–1607] proposed and studied estimators for integral curves based on noisy data of the corresponding gradient vector field. That estimation problem was motivated by diffusion tensor imaging, a popular brain imaging technique. Recently Sakhanenko [Theory Probab. Appl., 54 (2009), pp. 166–177] showed that those estimates have pointwise optimal convergence rate in a minimax sense.



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