To analyze the investigation of the application effects of different doses of dexmedetomidine (Dex) with combined spinal and epidural anesthesia nursing on analgesia after transurethral resection of prostate (TURP) by intelligent algorithm-based magnetic resonance imaging (MRI), MRI imaging segmentation model of mask regions with convolutional neural network (Mask R-CNN) features was proposed in the research. Besides, the segmentation effects of Mask R-CNN, U-net, and V-net algorithms were compared and analyzed. Meanwhile, a total of 184 patients receiving TURP were selected as the research objects, and they were divided into A, B, C, and D groups based on random number table method, each group including 46 cases. Patients in each group were offered different doses of Dex, and visual analogue scale (VAS) and Ramsay scores of different follow-up visit time, use of other analgesics, the incidence of postoperative cystospasm, and nursing satisfaction of patients in four groups were compared. The results demonstrated that Dice similarity coefficient (DSC) value, specificity, and positive predictive value of Mask R-CNN algorithm were 0.623 ± 0.084, 98.61%, and 69.57%, respectively, all of which were higher than those of U-net and V-net algorithms. Pain VAS scores and the incidence of cystospasm at different time periods of groups B and C were both significantly lower than those of group D ( < 0.05). Ramsay scores of groups B and C at 8 hours, 12 hours, 24 hours, and 48 hours after the operation were all remarkably higher than those in group D ( < 0.05). Besides, nursing satisfaction of groups B and C was obviously superior to that in group D, and the difference demonstrated statistical meaning ( < 0.05). The differences revealed that Dex showed excellent analgesic and sedative effects and could effectively reduce the incidence of complications after TURP, including cystospasm and nausea. In addition, it helped improve nursing satisfaction and patient prognosis.