GFF: Gated Fully Fusion for Semantic Segmentation

Semantic segmentation generates comprehensive understanding of scenes through densely predicting the category for each pixel. High-level features from Deep Convolutional Neural Networks already demonstrate their effectiveness in semantic segmentation tasks, however the coarse resolution of high-level features often leads to inferior results for small/thin objects where detailed information is important. It is natural to consider importing low level features to compensate for the lost detailed information in high-level features.Unfortunately, simply combining multi-level features suffers from the semantic gap among them. In this paper, we propose a new architecture, named Gated Fully Fusion (GFF), to selectively fuse features from multiple levels using gates in a fully connected way. Specifically, features at each level are enhanced by higher-level features with stronger semantics and lower-level features with more details, and gates are used to control the propagation of useful information which significantly reduces the noises during fusion. We achieve the state of the art results on four challenging scene parsing datasets including Cityscapes, Pascal Context, COCO-stuff and ADE20K.Comment: accepted by AAAI-2020(oral

Effects of propranolol in combination with radiation on apoptosis and survival of gastric cancer cells <it>in vitro</it>

<p>Abstract</p> <p>Background</p> <p>The National Comprehensive Cancer Network (NCCN) guidelines recommend radiotherapy as a standard treatment for patients with a high risk of recurrence in gastric cancer. Because gastric cancer demonstrates limited sensitivity to radiotherapy, a radiosensitizer might therefore be useful to enhance the radiosensitivity of patients with advanced gastric carcinoma. In this study, we evaluated if propranolol, a β-adrenoceptor (β-AR) antagonist, could enhance radiosensitivity and explored its precise molecular mechanism in gastric cancer cells.</p> <p>Methods</p> <p>Human gastric adenocarcinoma cell lines (SGC-7901 and BGC-823) were treated with or without propranolol and exposed to radiation. Cell viability and clonogenic survival assays were performed, and cell apoptosis was evaluated with flow cytometry. In addition, the expression of nuclear factor κB (NF-κB), vascular endothelial growth factor (VEGF), cyclooxygenase 2 (COX-2), and epidermal growth factor receptor (EGFR) were detected by western blot and real-time reverse transcription polymerase chain reaction (PCR).</p> <p>Results</p> <p>Propranolol combined with radiation decreased cell viability and clonogenic survivability. Furthermore, it also induced apoptosis in both cell lines tested, as determined by Annexin V staining. In addition, treatment with propranolol decreased the level of NF-κB and, subsequently, down-regulated VEGF, COX-2, and EGFR expression.</p> <p>Conclusions</p> <p>Taken together, these results suggested that propranolol enhanced the sensitivity of gastric cancer cells to radiation through the inhibition of β-ARs and the downstream NF-κB-VEGF/EGFR/COX-2 pathway.</p