HADCNet: Automatic segmentation of COVID-19 infection based on a hybrid attention dense connected network with dilated convolution.

the automatic segmentation of lung infections in CT slices provides a rapid and effective strategy for diagnosing, treating, and assessing COVID-19 cases. However, the segmentation of the infected areas presents several difficulties, including high intraclass variability and interclass similarity among infected areas, as well as blurred edges and low contrast. Therefore, we propose HADCNet, a deep learning framework that segments lung infections based on a dual hybrid attention strategy. HADCNet uses an encoder hybrid attention module to integrate feature information at different scales across the peer hierarchy to refine the feature map. Furthermore, a decoder hybrid attention module uses an improved skip connection to embed the semantic information of higher-level features into lower-level features by integrating multi-scale contextual structures and assigning the spatial information of lower-level features to higher-level features, thereby capturing the contextual dependencies of lesion features across levels and refining the semantic structure, which reduces the semantic gap between feature maps at different levels and improves the model segmentation performance. We conducted fivefold cross-validations of our model on four publicly available datasets, with final mean Dice scores of 0.792, 0.796, 0.785, and 0.723. These results show that the proposed model outperforms popular state-of-the-art semantic segmentation methods and indicate its potential use in the diagnosis and treatment of COVID-19.

Bordetella avium-associated endophthalmitis: case report.

BACKGROUND: Bordetella avium, an aerobic bacterium that rarely causes infection in humans, is a species of Bordetella that generally inhabits the respiratory tracts of turkeys and other birds. It causes a highly contagious bordetellosis. Few reports describe B. avium as a causative agent of eye-related infections. CASE PRESENTATION: We report a case of acute infectious endophthalmitis associated with infection by B. avium after open trauma. After emergency vitrectomy and subsequent broad-spectrum antibiotic treatment, the infection was controlled successfully, and the patient's vision improved. CONCLUSIONS: B. avium can cause infection in the human eye, which can manifest as acute purulent endophthalmitis. Nanopore targeted sequencing technology can quickly identify this organism. Emergency vitrectomy combined with lens removal and silicone oil tamponade and the early application of broad-spectrum antibiotics are key for successful treatment.