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The SSQ ratio maps are transformed into Talairach space using these transformations.
Instead, we will consider it when using these transformations in the molecular optimization process, which is often the ultimate goal of the MMP analysis.
Using these transformations, the weighted sum rate optimization problem in (29a)–(29e) can be recast in the following convex format: (35).
Using these transformations, we propose a BALM for the Signorini boundary value problem, which only needs the iteration for boundary function and the computation of the boundary variational equation.
The advantages of using these transformations are that additional sources of variation may be easily incorporated, and parameter estimation may be improved.
Using these transformations, an average image is computed.
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16 The lesion maps were transferred to the T1-weighted images using these transformation matrices.
We use these transformations to define data-sensitive BIP architectures and their composition.
The importance of obtaining a transformed equation of exactly the same form as the original equation, is that ultimately we will (in a sequel to the current paper) use these transformations to establish a hierarchy of boundary value problems with (1.1) and various boundary conditions; see [4] for the differential equations case.
We also used these transformations to calculate the Cα RMSD between the motif and context residues of the native and chimera protein pairs.
To compare the distribution of cells across brains, we aligned the autofluorescence image captured from each brain to a common 'reference space' and used these transformations to align each set of centroids into this common space (see 'Materials and methods').
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