Fast and Interpretable Nonlocal Neural Networks for Image Denoising via Group-Sparse Convolutional Dictionary Learning

Nonlocal self-similarity within natural images has become an increasingly popular prior in deep-learning models. Despite their successful image restoration performance, such models remain largely uninterpretable due to their black-box construction. Our previous studies have shown that interpretable construction of a fully convolutional denoiser (CDLNet), with performance on par with state-of-the-art black-box counterparts, is achievable by unrolling a dictionary learning algorithm. In this manuscript, we seek an interpretable construction of a convolutional network with a nonlocal self-similarity prior that performs on par with black-box nonlocal models. We show that such an architecture can be effectively achieved by upgrading the $\ell 1$ sparsity prior of CDLNet to a weighted group-sparsity prior. From this formulation, we propose a novel sliding-window nonlocal operation, enabled by sparse array arithmetic. In addition to competitive performance with black-box nonlocal DNNs, we demonstrate the proposed sliding-window sparse attention enables inference speeds greater than an order of magnitude faster than its competitors.Comment: 11 pages, 8 figures, 6 table

Effect of root canal rinsing protocol on dentin bond strength of two resin cements using three different method of test

Background: Different studies have used different tests to evaluate bond strength of resin cements to root dentin. In this in vitro study, three different tests were used to evaluate the bond strength of two resin cements to root dentin using two root dentin irrigation protocols. Material and Methods: Ninety-six intact single-rooted teeth were selected for this study. Forty-eight teeth, with a root length of 15mm, were randomly divided into two groups and irrigated with normal saline or 2.5% sodium hypochlorite solutions during root canal preparation, respectively. For each 12 specimens from each group, fiber post #1 was bonded using an etch-and-rinse (Duo-Link) and a self-adhesive (BisCem) resin cement, respectively. After incubation, two specimens were prepared for the push-out test from the middle thirds of the roots. In another 24 teeth, after two 1.5-mm sections were prepared from the middle thirds of the prepared roots, sections of the post were bonded in two subgroups with each of the cements mentioned above and the samples were prepared for the pull-out test. For shear test, the crowns of 48 teeth were cut away, the dentin surfaces were prepared, the two irrigation solutions were used, and the resin cements were bonded. Data collected from the three tests were evaluated by ANOVA, post-hoc Tukey and Weibull tests (α=0.05). Results: There were significant differences in the mean bond strength values between the three bond strength tests (P<0.001). Rinsing protocol and cement type resulted in similar variations in the mean bond strength in all tests (P>0.05). Conclusions: Under the limitations of the present study, the method of the test used had an effect on the recorded bond strength between the resin cement and root dentin. Cement type and irrigation protocol resulted in similar variations with all the tests. Push-out and shear tests exhibited more coherent results