PubMed · 778881
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P Slade. 1976. Editorial: Hallucinations.. https://doi.org/10.1017/s0033291700007431
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Currently, images acquired via magnetic resonance imaging (MRI) and functional magnetic resonance imaging (fMRI) technology are reconstructed using the discrete inverse Fourier transform. While computationally convenient, this approach is not able to filter out noise. This is a serious limitation because the amount of noise in MRI and fMRI can be substantial. In this paper, we propose an alternative approach to reconstruction, based on penalized likelihood methodology. In particular, we focus on non-linear shrinkage estimators and show that this approach achieves a great reduction in integrated mean squared error (IMSE) of the estimated image with respect to the currently used estimator. This approach is extremely fast and easy to implement computationally. In addition, it can be combined with various alternative approaches to MR image reconstruction and can be easily adapted to other, non-MRI contexts, in which the observed data and the quantities of interest are related via a linear transform.
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Stem cells, by virtue of their defining property of self-renewal, represent an unlimited source of potentially functional human cells for basic research and regenerative medicine. Having validated the feasibility of cell-based therapeutic strategies over the past decade, mostly through the use of rodent cells, the stem cell field has now embarked upon a detailed characterization of human cells. Recent progress has included improved cell culture conditions, long-term propagation, directed differentiation, and transplantation of both human embryonic and somatic stem cells. Continued progress in understanding basic human stem cell biology, combined with a better handle on the fundamental pathophysiology of human diseases one wishes to target (including the use of human stem cells in primate and other large animal models of human disease), should help to move this technology closer to clinical application.