Effect of three surface conditioning methods to improve bond strength of particulate filler resin composites

The use of resin-based composite materials in operative dentistry is increasing, including applications in stress-bearing areas. However, composite restorations, in common with all restorations, suffer from deterioration and degradation in clinical service. Durable repair alternatives by layering a new composite onto such failed composite restorations, will eliminate unnecessary loss of tooth tissue and repeated insults to the pulp. The objective of this study was to evaluate the effect of three surface conditioning methods on the repair bond strength of a particulate filler resin-composite (PFC) to 5 PFC substrates. The specimens were randomly assigned to one of the following surface conditioning methods: (1) Hydrofluoric (HF) acid gel (9.5%) etching, (2) Air-borne particle abrasion (50 mum Al2O3), (3) Silica coating (30 mum SiOx, CoJet(R)-Sand). After each conditioning method, a silane coupling agent was applied. Adhesive resin was then applied in a thin layer and light polymerized. The low-viscosity diacrylate resin composite was bonded to the conditioned substrates in polyethylene molds. All specimens were tested in dry and thermocycled (6.000, 5-55 degreesC, 30 s) conditions. One-way ANOVA showed significant influence of the surface conditioning methods (p &lt;0.001), and the PFC types (p &lt;0.0001) on the shear bond strength values. Significant differences were observed in bond strength values between the acid etched specimens (5.7-14.3 MPa) and those treated with either air-borne particle abrasion (13.0-22.5 MPa) or silica coating (25.5-41.8 MPa) in dry conditions (ANOVA, p &lt;0.001). After thermocycling, the silica coating process resulted in the highest bond values in all material groups (17.2-30.3 MPa). (C) 2005 Springer Science + Business Media, Inc.</p

QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data

Optical coherence tomography (OCT) enables high-resolution and non-invasive 3D imaging of the human retina but is inherently impaired by speckle noise. This paper introduces a spatio-temporal denoising algorithm for OCT data on a B-scan level using a novel quantile sparse image (QuaSI) prior. To remove speckle noise while preserving image structures of diagnostic relevance, we implement our QuaSI prior via median filter regularization coupled with a Huber data fidelity model in a variational approach. For efficient energy minimization, we develop an alternating direction method of multipliers (ADMM) scheme using a linearization of median filtering. Our spatio-temporal method can handle both, denoising of single B-scans and temporally consecutive B-scans, to gain volumetric OCT data with enhanced signal-to-noise ratio. Our algorithm based on 4 B-scans only achieved comparable performance to averaging 13 B-scans and outperformed other current denoising methods.Comment: submitted to MICCAI'1