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Transmission spectra of wet human teeth and dentin slices, together with blood of different flow rates were investigated. The measurements carried out over a wide spectral range, from visible light down to terahertz radiation. The results make it possible to find the optimum light frequency for an all-optical determination of pulpal blood flow and, consequently, for clinically diagnosis of tooth vitality.
Transmission spectra of wet human teeth and dentin slices, together with blood of different flow rates were investigated. The measurements carried out over a wide spectral range, from visible light down to terahertz radiation. The results make it possible to find the optimum light frequency for an all-optical determination of pulpal blood flow and, consequently, for clinically diagnosis of tooth vitality.
Transmission spectra of wet human teeth and dentin slices, together with blood of different flow rates were investigated over a wide spectral range, from visible to terahertz (THz) light. The results make it possible to find the optimum light frequency for an all-optical determination of pulpal blood flow and, consequently, for clinically diagnosis of tooth vitality.
PPG signal acquisition and analysis on in vitro tooth model for dental pulp vitality assessmen
(2012)
Object
The consistency of parametric registration in multi-temporal magnetic resonance (MR) imaging studies was evaluated.
Materials and methods
Serial MRI scans of adult patients with a brain tumor (glioma) were aligned by parametric registration. The performance of low-order spatial alignment (6/9/12 degrees of freedom) of different 3D serial MR-weighted images is evaluated. A registration protocol for the alignment of all images to one reference coordinate system at baseline is presented. Registration results were evaluated for both, multimodal intra-timepoint and mono-modal multi-temporal registration. The latter case might present a challenge to automatic intensity-based registration algorithms due to ill-defined correspondences. The performance of our algorithm was assessed by testing the inverse registration consistency. Four different similarity measures were evaluated to assess consistency.
Results
Careful visual inspection suggests that images are well aligned, but their consistency may be imperfect. Sub-voxel inconsistency within the brain was found for allsimilarity measures used for parametric multi-temporal registration. T1-weighted images were most reliable for establishing spatial correspondence between different timepoints.
Conclusions
The parametric registration algorithm is feasible for use in this application. The sub-voxel resolution mean displacement error of registration transformations demonstrates that the algorithm converges to an almost identical solution for forward and reverse registration.