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A novel technique to incorporate structural prior information into multi-modal tomographic reconstruction

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Academic year: 2019

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Figure 1. An example of local geometrical structure represented by two diffusion tensorsfor anatomical μ and emission images λ respectively
Table 1. Parameters for the image restoration experiment.
Figure 3. Recovered image λˆ using (a) DT filter (30), (b) BM (32) (c) CDT filter (31).In (b) the boundaries which are common to both λ and μ are enhanced significantly.However, in places where misalignment of data exist, very strong artefacts appearedand fea
Figure 5. Bias-CoV (left) plots for the gray matter (GM) ROI and bias-CoV (right) forthe hot lesion ROI (indicated by arrows in figure 6).
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