ABSTRACT
Binocular endoscopy is gradually becoming the future of minimally invasive surgery (MIS) thanks to the development of stereo vision. However, some problems still exist, such as the low reconstruction accuracy, small surgical field, and low computational efficiency. To solve these problems, we designed a framework for real-time dense reconstruction in binocular endoscopy scenes. First, we obtained the initial disparity map using an SGBM algorithm and proposed the disparity confidence map as a dataset to provide StereoNet training. Then, based on the depth map predicted by StereoNet, the corresponding left image of each depth map was input into the Oriented Fast and Brief-Simultaneous Localization and Mapping (ORB-SLAM) framework using an RGB-D camera to realize the real-time dense reconstruction of the binocular endoscopy scene. The proposed algorithm was verified in the stomach phantom and a real pig stomach. Compared with the ground truth, the proposed algorithm's RMSE is 1.620 mm, and the number of effective points in the point cloud is 834,650, which is a significant improvement in the mapping ability compared with binocular SLAM and ensures the real-time performance of the algorithm while performing dense reconstruction. The effectiveness of the proposed algorithm is verified.
ABSTRACT
The complex interactions between climate and watershed characteristics lead to diverse annual runoff responses. Understanding the mechanism by which different climatic and watershed factors affect annual runoff is helpful in understanding the resulting changes in the hydrological process. In this study, the characteristics of 73 watersheds were analyzed. The basins were divided into three categories according to their climatic regions: temperate continental climate (n = 7); temperate monsoon climate(n = 36); and subtropical monsoon climate(n = 30). Correlation analysis, linear regression, and path analysis were used to quantify the effects of selected watershed characteristics and meteorological conditions on long-term runoff. Results showed that the average annual runoff coefficient was strongly correlated with basin area, showing a scale effect. The average annual runoff depth was strongly positively correlated with precipitation for the all watersheds. As the drought index (DI, the ratio of annual evaporation capacity to annual precipitation) increased, the annual runoff depth decreased logarithmically. The average annual rainfall and runoff depth of watersheds in the subtropical monsoon climate zone were significantly higher than those in other climatic zones, and there was no significant difference in potential evaporation between the temperate monsoon climate and subtropical monsoon climate zones. With increases in both the drought index (Ep/P) and moisture index (E/P), the vegetation distribution in the basin showed an increasing trend in farmland area and decreasing trend in forest area. Path analysis showed that rainfall had a positive effect on annual average runoff depth (ranging from 31 to 62%) while actual evapotranspiration had a negative impact (ranging from 17 to 47%). For all basins, a negative effect (13-25%) of basin area on runoff depth was observed, while forestland area had a positive effect (7-39%) on runoff depth. This study further quantified the effects of climatic and geographical factors on the long-term water balance in different climatic regions.