Foreground segmentation network using transposed convolutional neural networks and up sampling for multiscale feature encoding.

Foreground segmentation algorithm aims to precisely separate moving objects from the background in various environments. However, the interference from darkness, dynamic background information, and camera jitter makes it still challenging to build a decent detection network. To solve these issues, a triplet CNN and Transposed Convolutional Neural Network (TCNN) are created by attaching a Features Pooling Module (FPM). TCNN process reduces the amount of multi-scale inputs to the network by fusing features into the Foreground Segmentation Network (FgSegNet) based FPM, which extracts multi-scale features from images and builds a strong feature pooling. Additionally, the up-sampling network is added to the proposed technique, which is used to up-sample the abstract image representation, so that its spatial dimensions match with the input image. The large context and long-range dependencies among pixels are acquired by TCNN and segmentation mask, in multiple scales using triplet CNN, to enhance the foreground segmentation of FgSegNet. The results, clearly show that FgSegNet surpasses other state-of-the-art algorithms on the CDnet2014 datasets, with an average F-Measure of 0.9804, precision of 0.9801, PWC as (0.0461), and recall as (0.9896). Moreover, the FgSegNet with up-sampling achieves the F-measure of 0.9804 which is higher when compared to the FgSegNet without up-sampling.

Disease Course and Response to Immunotherapy in Children With Childhood Disintegrative Disorder: A Retrospective Case Series.

Childhood disintegrative disorder is a poorly understood neurobehavioral disorder of early childhood characterized by acute to subacute profound regression in previously developed language, social behavior, and adaptive functions. The etiology of childhood disintegrative disorder remains unknown and treatment is focused on symptomatic management. Interest in neuroinflammatory mechanisms has grown with the increased recognition of autoimmune brain diseases and similarities between the presenting symptoms of childhood disintegrative disorder and pediatric autoimmune encephalitis. Importantly, a diagnosis of pediatric autoimmune encephalitis requires evidence of inflammation on paraclinical testing, which is absent in childhood disintegrative disorder. Here we report 5 children with childhood disintegrative disorder who were initially diagnosed with possible autoimmune encephalitis and treated with immunotherapy. Two children had provocative improvements, whereas 3 did not change significantly on immunotherapy. Additionally, a sixth patient with childhood disintegrative disorder evaluated in our Autoimmune Brain Disease Clinic showed spontaneous improvement and is included to highlight the variable natural history of childhood disintegrative disorder that may mimic treatment responsiveness.

Effectiveness of laser fluorescence-based device in detecting the extent of re-mineralisation in primary teeth compared to the conventional method: An In vitro study.

Background: Laser fluorescence (LF)-based clinical device DIAGNOdent™ is at present being used to detect caries. Can the same be used to detect therapeutic remineralisation of early white spot lesions? Aims: To explore the feasibility of using LF-based device in monitoring the changes following remineralisation of demineralised primary teeth. Materials and Method: The sample number for the present experimental in vitro study was 10. The LF based device readings were correlated with surface microhardness (SMH) test values to evaluate its efficiency. SMH analysis was performed using a microhardness tester (Tescol-HT1000AD). All the samples were demineralised, followed by remineralisation using fluoride varnish and pH cycling. The data was analysed using the Statistical Package for the Social Sciences (SPSS) version 17.0 (IBM SPSS®) software. Paired t-test was performed to compare laser fluorescence readings and SMH test result values at baseline, after demineralisation, and after remineralisation. Pearson's correlation was used to compare the relation between the laser fluorescence and SMH test. Results: A good negative correlation was seen between the two methods at the baseline readings even though it was not statistically significant (P = 0.069). A positive correlation between the methods existed following demineralisation which was not significant (P = 0.074). The correlation between the parameters following remineralisation showed a moderate negative correlation but was not significant (P = 0.55). Conclusion: DIAGNOdent™ values at baseline, after demineralisation, and after remineralisation was consistent with SMH values. Thus, DIAGNOdent™ can be explored to provide chairside assistance in identifying remineralisation of white spot lesions.