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We propose two types of subject-dependent classification strategies to combine the information of both modalities.
We learned separate CNN weights and algorithmic parameters for the cases of confocal images, split detector images, and a combination of both modalities.
The time to puncture, time to introduction of wire, quality of puncture (judged on fluoroscopy) and global rating of both modalities were documented.
The BrainPET scanner from Siemens, designed as hybrid MR/PET system for simultaneous acquisition of both modalities, provides high-resolution PET images with an optimum resolution of 3 mm.
However, there is already evidence that a combination of both modalities might provide added value [72].
As audiovisual quality is the integration of both modalities, similar perceptual effects were observed.
The intensity maxima of both modalities were (61±51) mm distant from each other.
We can observe an increasing precision score for descriptors of both modalities along iterations.
The accuracies of both modalities were calculated by binary classification testing.
To this end, we first estimate a rough alignment of the coordinate systems of both modalities.
In this study, image patches of both modalities (PET and CT) were mixed into the same network.
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