Naoko Uemoto

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Artificial neural networks can be exploited to solve inverse problems arising from the estimation of neural activities in the brain. In this paper, we review the network inversion techniques for solving inverse problems with special attention directed towards electroencephalographic dipole localization and the improvement of positron emission tomography. In(More)
In PET image analysis, conventional deconvolution alone will not give sufficient information for a precise study of a localized brain function. In the deconvolution process, which is a type of inverse problem, it is important to confine the solution space by incorporating a priori knowledge such as the tissue distribution given by MR images as well as(More)
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