This study was to explore the application value for central venous stenosis and occlusion in hemodialysis patients under the CT angiography based on intelligent segmentation algorithm, so that patients can survive better. Spiral CT was used to examine upper limb swelling in 62 uremic hemodialysis patients at a speed of 3.8 mL/s. Nonionic iodine contrast agent was injected around the contralateral limb. The total dosage of 90-102 mL, it was scanned by intelligent trigger technology. The trigger scanning threshold was set. The monitoring point was located in the superior vena cava. CT with convolutional neural network intelligent segmentation algorithm was used to process image data. Finally, the quality of life and related biochemical levels of patients before and after hemodialysis were detected. Under the CT angiography of intelligent segmentation algorithm, 77 stenoses were found in 62 uremic patients, including 48 stenoses of the brachial vein and 17 stenoses of the superior vena cava. The correlation coefficient between CT angiography and digital subtraction angiography (DSA) imaging results of intelligent segmentation algorithm was 0.411. Segmentation effect of the algorithm in this study: automatic segmentation accuracy was greater than 79%. After hemodialysis treatment, the scores of physical fitness, pain, social function, and energy status of patients were significantly increased compared with those before treatment, and the levels of albumin, serum phosphorus, and parathyroid hormone were significantly decreased ( P < 0.05 ). In summary, CT angiography with intelligent segmentation algorithm can obtain clear, intuitive, and complete vascular walking images, and better display subclavian vein, brachiocephalic vein, and superior vena cava. It can provide more valuable support for surgical intervention and has certain application value for better survival of hemodialysis patients.