ABSTRACT
Remote sensing images are inevitably affected by the degradation of haze with complex appearance and non-uniform distribution, which remarkably affects the effectiveness of downstream remote sensing visual tasks. However, most current methods principally operate in the original pixel space of the image, which hinders the exploration of the frequency characteristics of remote sensing images, resulting in these models failing to fully exploit their representation ability to produce high-quality images. This paper proposes a frequency-oriented remote sensing dehazing Transformer named FOTformer, to explore information in the frequency domain to eliminate disturbances caused by haze in remote sensing images. It contains three components. Specifically, we developed a frequency-prompt attention evaluator to estimate the self-correlation of features in the frequency domain rather than the spatial domain, improving the image restoration performance. We propose a content reconstruction feed-forward network that captures information between different scales in features and integrates and processes global frequency domain information and local multi-scale spatial information in Fourier space to reconstruct the global content under the guidance of the amplitude spectrum. We designed a spatial-frequency aggregation block to exchange and fuse features from the frequency domain and spatial domain of the encoder and decoder to facilitate the propagation of features from the encoder stream to the decoder and alleviate the problem of information loss in the network. The experimental results show that the FOTformer achieved a more competitive performance against other remote sensing dehazing methods on commonly used benchmark datasets.
ABSTRACT
Background: The endoscopic nasojejunal (NJ) placement plays a pivotal role in the nutritional support of critically ill patients. However, the conventional endoscopy-guided tube insertion method presents issues of excessive procedural duration. We have enhanced the traditional endoscopy-guided catheter placement method, enabling a faster and more convenient catheter insertion. Methods: We improved the traditional endoscopically guided technique by incorporating an extra silk thread knot at the 25 cm mark on the jejunal segment of the NJ tube to assist endoscopists in accurate tube placement. We conducted the improved NJ tube placement on critically ill patients in need of enteral nutrition (EN). Laboratory data were retrospectively collected before and after the 7-day period of NJ tube placement and EN treatment to evaluate the effectiveness and safety of the improved method. Results: A total of 88 critically ill patients, with an average age of 59.6±15.5 years, and a male ratio of 86.4%, who underwent the improved NJ tube placement method were enrolled into analysis finally, achieving a 100% success rate of NJ tube insertion. The average time for tube insertion was 5.9±2.2 min, with a mean insertion depth of 108.8±12.5 cm. The EN tolerance score was 0.79±0.98. Following 7 days of EN therapy, the patients showed significant improvement in serum albumin levels compared to baseline (36.42 vs. 33.66 g/L, P<0.001). Conclusions: The improved endoscopically guided NJ tube placement technique is a rapid and safe procedure with excellent patient tolerance. It significantly improves the nutritional status of critically ill patients and facilitates the administration of EN, which requires further validation through randomized controlled trials.
