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This work aimed to explore the application value of intelligent region of interest (ROI) detection algorithm in evaluating renal dynamic imaging information data of renal function in patients with chronic heart failure (CHF). 52 patients with CHF were selected as the research objects and grouped according to the level of renal function into an experimental group (14 cases) and an observation group (38 cases). In addition, 10 healthy people were selected as the research objects, as the control group. Different calculation methods of glomerular filtration rate (GFR) were used to evaluate the renal function of patients, and the ROI detection algorithm-assisted delineation was compared with traditional manual delineation. It was found that the GFR of the experimental group calculated by different methods was 52.58 mL/min/1.73m2 and 43.77 mL/min/1.73m2, respectively, which was significantly lower than that of the observation group ( P &lt; 0.05 ), and that in both groups was lower than that of the control group ( P &lt; 0.05 ). In addition, the unilateral renal function values of the two auxiliary delineations were both 13.61 mL/min/1.73 m2, while the results of the two manual delineations were significantly different ( P &lt; 0.05 ). Therefore, renal dynamic imaging based on the ROI detection algorithm to evaluate the renal function of CHF patients showed a great improvement in effectiveness, sensitivity, stability, and efficiency compared with the traditional manual delineation, which was worthy of clinical promotion.

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Renal Dynamic Imaging Information Data in the Evaluation of Renal Function in Patients with Chronic Heart Failure under the Guidance of Intelligent Region of Interest Detection Algorithm