Skeleton-guided multi-scale dual-coordinate attention aggregation network for retinal blood vessel segmentation.

Deep learning plays a pivotal role in retinal blood vessel segmentation for medical diagnosis. Despite their significant efficacy, these techniques face two major challenges. Firstly, they often neglect the severe class imbalance in fundus images, where thin vessels in the foreground are proportionally minimal.

BCR-UNet: Bi-directional ConvLSTM residual U-Net for retinal blood vessel segmentation.

Background: High precision segmentation of retinal blood vessels from retinal images is a significant step for doctors to diagnose many diseases such as glaucoma and cardiovascular diseases. However, at the peripheral region of vessels, previous U-Net-based segmentation methods failed to significantly preserve the low-contrast tiny vessels.

Methods: For solving this challenge, we propose a novel network model called Bi-directional ConvLSTM Residual U-Net (BCR-UNet), which takes full advantage of U-Net, Dropblock, Residual convolution and Bi-directional ConvLSTM (BConvLSTM).

Influence of periodontal repair on the quality of prosthodontics and postoperative adverse events.

Objective: To investigate the influence of periodontal repair on the oral cavity and postoperative adverse events.

Methods: From June 2017 to June 2019, 96 patients with prosthodontics were selected as the research participants. According to the intervention scheme, the patients were grouped into the observation group (OG, 51 cases with periodontal repair combined with prosthodontics) and the control group (CG, 45 cases with prosthodontics).

Chemical characterization of a PD-1/PD-L1 inhibitory activity fraction of the ethanol extract from .

Searching for PD-1/PD-L1 inhibitor from medicinal plants has become a potential method to discover small molecular cancer immunotherapy drugs. Using PD-1/PD-L1 inhibitory activity assay , a bioactive fraction was obtained from the ethanol extract of . A sensitive UPLC-HRMS/MS method was established for the rapid screening and identification of compositions from bioactive fraction.