Colorectal polyps are important early markers of colorectal cancer, and their early detection is crucial for cancer prevention. Although existing polyp segmentation models have achieved certain results, they still face challenges such as diverse polyp morphology, blurred boundaries, and insufficient feature extraction. To address these issues, this study proposes a parallel coordinate fusion network (PCFNet), aiming to improve the accuracy and robustness of polyp segmentation. PCFNet integrates parallel convolutional modules and a coordinate attention mechanism, enabling the preservation of global feature information while precisely capturing detailed features, thereby effectively segmenting polyps with complex boundaries. Experimental results on Kvasir-SEG and CVC-ClinicDB demonstrate the outstanding performance of PCFNet across multiple metrics. Specifically, on the Kvasir-SEG dataset, PCFNet achieved an F1-score of 0.897 4 and a mean intersection over union (mIoU) of 0.835 8; on the CVC-ClinicDB dataset, it attained an F1-score of 0.939 8 and an mIoU of 0.892 3. Compared with other methods, PCFNet shows significant improvements across all performance metrics, particularly in multi-scale feature fusion and spatial information capture, demonstrating its innovativeness. The proposed method provides a more reliable AI-assisted diagnostic tool for early colorectal cancer screening.
Humans ; Colonic Polyps/diagnostic imaging* ; Colorectal Neoplasms/diagnostic imaging* ; Neural Networks, Computer ; Image Processing, Computer-Assisted/methods* ; Algorithms ; Early Detection of Cancer

Objective:To investigate the dynamic change of nutritional risk in hepatological surgical patients during hospitalization.Methods:Anthropometric measurement and laboratory examination were conducted within 24 hours both after admission and before discharge. NRS 2002 was used to assess patients' nutritional status. The correlation between nutritional status and clinical outcomes was also analyzed.Results:A total of 600 patients were included in the study, among whom 401 were with benign diseases and 199 with malignant tumors. Compared with those values at admission, patients' weight, BMI, grip strength, calf circumference and main serum protein indicators decreased significantly at discharge ( P<0.05). The incidence of nutritional risk at discharge was 57.3%, higher than that at admission ( χ 2=6.512, P=0.011). The incidence of nutritional risk showed a significant increase during hospitalization in hepatological surgery patients ( P<0.05). Conclusions:Hepatological surgery patients were at high nutritional risk, which increased during hospitalization. The whole-course nutrition management of surgical patients should be given more attention.