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Human values for DT are estimated by fitting a growth model to imaging data reported in the literature, see Additional file 1: Table S2.
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The combination of these 3 techniques represents a novel method for exploring brain connectivity in postmortem brain specimens from virtually any species, although it is currently most practical in small animal models due to imaging hardware and scan time requirements.
Applying the Finke model to our imaging kinetics allowed us to determine the rate constants of nucleation and autocatalytic growth.
For the association analysis, we used a mass univariate model for pathway-based approaches to imaging genetics association studies as previously described by Inkster et al. (2010).
This primary finding of principal component analysis was refined by exploiting within groups the relationship of the PC7, relevant for frontal cortex processing, to the verbal memory functions, the so-called scaled subprofile model to functional imaging [ 31].
In our experiment, we used prediction errors estimated from the model and applied it as one of the regressors in a general linear model (GLM) to imaging data.
The laying hen may be a suitable model to test new imaging agents and develop targeted anti-OVCA therapeutics.
Monte Carlo simulations are used in nuclear medicine to model imaging systems and develop and assess tomographic reconstruction algorithms and correction methods for improved image quantification.
A striatal phantom was used to model DAT imaging.
Recently, we described the application of this model to diffuse optical imaging [ 14].
Keelan et al. performed a study with In-labelled anti-E-selectin monoclonal antibody (1.2B6) in an animal model to assess the imaging potential of the antibody [ 74].
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