Toward accurate polyp segmentation with cascade boundary-guided attention

In clinical practice, accurate polyp segmentation provides important information for the early detection of colorectal cancer. Benefiting from the advancement of deep learning techniques, various neural networks have been developed for polyp segmentation. However, most state-of-the-art methods have suffered from the challenge of precisely segmenting polyps with clear boundaries. To tackle this challenge, in this paper, we propose a novel and effective cascade boundary-guided attention network based on an encoder-decoder framework. Specifically, instead of just using the addition of shallow and deep features, the fine-grained boundary information is explicitly introduced into the skip connection of encoder and decoder layers to achieve accurate polyp segmentation. Moreover, the cascade refinement strategy is utilized into the multi-stage enhancement of boundary features to progressively produce better predictions. Extensive evaluations on five public benchmark datasets show that our method outperforms state-of-the-arts on various polyp segmentation tasks. Further experiments conducted on the cross-dataset (training on one dataset and testing on another dataset) validate the generalization ability of the proposed method

Spatial-temporal patterns and influencing factors for hemorrhagic fever with renal syndrome: A 16-year national surveillance analysis in China

Background: China is confronted with the significant menace posed by hemorrhagic fever with renal syndrome (HFRS). Nevertheless, the long-term spatial-temporal variations, regional prevalence patterns, and fundamental determinants' mechanisms for HFRS remain inadequately elucidated. Methods: Newly diagnosed cases of HFRS from January 2004 to December 2019 were acquired from the China Public Health Science Data repository. We used Age-period-cohort and Bayesian Spacetime Hierarchy models to identify high-risk populations and regions in mainland China. Additionally, the Geographical Detector model was employed to quantify the determinant powers of significant driver factors to the disease. Results: A total of 199,799 cases of HFRS were reported in mainland China during 2004–2019. The incidence of HFRS declined from 1.93 per 100,000 in 2004 to 0.69 per 100,000 in 2019. The incidence demonstrated an inverted U-shaped trend with advancing age, peaking in the 50–54 age group, with higher incidences observed among individuals aged 20–74 years. Hyperendemic areas were mainly concentrated in the northeastern regions of China, while some western provinces exhibited a potential upward trend. Geographical detector model identified that the spatial variations of HFRS were significantly associated with the relative humidity (Q = 0.36), forest cover (Q = 0.26), rainfall (Q = 0.18), temperature (Q = 0.16), and the surface water resources (Q = 0.14). Conclusions: This study offered comprehensive examinations of epidemic patterns, identified high-risk areas quantitatively, and analyzed factors influencing HFRS transmission in China. The findings may contribute to the necessary implementations for the effective prevention and control of HFRS