The retrieved evidence provides a low level of support for selection of AB or a bone substitute. Clear reasons could not be identified that should prompt the clinician to prefer AB or BS.

Oral Squamous Cell Carcinoma (OSCC) is a common type of cancer of the oral epithelium. Despite their high impact on mortality, sufficient screening methods for early diagnosis of OSCC often lack accuracy and thus OSCCs are mostly diagnosed at a late stage. Early detection and accurate outline estimation of OSCCs would lead to a better curative outcome and a reduction in recurrence rates after surgical treatment. Confocal Laser Endomicroscopy (CLE) records sub-surface micro-anatomical images for in vivo cell structure analysis. Recent CLE studies showed great prospects for a reliable, real-time ultrastructural imaging of OSCC in situ. We present and evaluate a novel automatic approach for OSCC diagnosis using deep learning technologies on CLE images. The method is compared against textural feature-based machine learning approaches that represent the current state of the art. For this work, CLE image sequences (7894 images) from patients diagnosed with OSCC were obtained from 4 specific locations in the oral cavity, including the OSCC lesion. The present approach is found to outperform the state of the art in CLE image recognition with an area under the curve (AUC) of 0.96 and a mean accuracy of 88.3% (sensitivity 86.6%, specificity 90%).

A biochemical characterization of pathologies in biological tissue can be provided by Raman spectroscopy. Often, the raw spectrum is severely affected by fluorescence interference. We report and compare various spectra-processing approaches required for the purification of Raman spectra from heavily fluorescence-interfered raw spectra according to the shifted-excitation Raman difference spectroscopy method. These approaches cover the entire spectra-processing chain from the raw spectra to the purified Raman spectra. In detail, we compared (1) area normalization versus z-score normalization, (2) direct reconstruction of the difference spectra versus reconstruction of zero-centered difference spectra and (3) collective baseline correction of the reconstructed spectra versus piecewise baseline correction of the reconstructed spectra and, finally, (4) analyzed the influence of the shift of the excitation wavelength on the quality of the reconstructed spectra. Statistical analysis of the spectra showed that -in our experiments -the best results were obtained for the z-score normalization before subtraction of the normalized spectra, followed by zero-centering of the difference spectra before reconstruction and a piecewise baseline correction of the pure Raman spectra. With our equipment, a wavelength shift from 784 to 785 nm provided reconstructed spectra of best quality. The analyzed specimens were different tissue types of pigs, tissue from the oral cavity of humans and a model solution of dye dissolved in ethanol.

PS yields significantly higher temperatures and thermal tissue alterations on load levels higher than 500 g and is significantly slower for ISP compared to SB and TB. For ISP with PS, a maximum load of 400 g should be maintained.