Evaluation of the Application Effect of Contrast-Enhanced Ultrasound Image Technology Based on Three-Dimensional Image Fusion Algorithm in the Diagnosis of Adenomyosis

In this paper, the effect of ultrasound images based on a 3-dimensional image fusion algorithm in the diagnosis of adenomyosis was evaluated. 88 patients with adenomyosis who were treated in the hospital from February 2019 to May 2020 were selected as the research subjects. They were rolled into localized type (Group A), with 40 cases, and diffuse type (Group B), with 48 cases. At the same time, 45 women of normal childbearing age who underwent physical examination in the outpatient clinic were rolled into the control group (Group C). Three-dimensional ultrasound scans of the uterus were performed on all patients, to observe the enhancement methods and characteristics. Then, the image characteristics of adenomyosis were studied through the time-intensity curve (TIC). Arise time ATs of three groups of patients were not different greatly ( P > 0.05 ). It was found that the enhancement method, enhancement uniformity, and enhancement level of ultrasound scan in Groups A and B were significantly different from Group C ( P < 0.05 ). In contrast with Group C, the rise time (RT) of the ultrasound scan of the two groups was less, the time-to-peak (TTP) was faster, and the image maximum (IMAX) was higher ( P < 0.05 ). What is more, contrast-enhanced ultrasonic (CEUS) detection in patients with adenomyosis showed centrality and nonuniform high enhancement. Besides, less RT, faster TTP, and higher IMAX than the normal population can be the key evidence for the clinical diagnosis of adenomyosis. In conclusion, according to the blood supply characteristics of adenomyosis and other gynecological diseases, the enhancement method and enhancement time of ultrasound images are significantly different. TIC can reflect the hemodynamic difference between the lesion and the normal ones. Therefore, the CEUS based on the three-dimensional image fusion algorithm can be applied to the image diagnosis of adenomyosis.