Abstract
This paper aimed to explore pelvic lymphadenectomy for gynecological malignant tumors guided by computed tomography angiography (CTA) images under region-growing algorithm (RGA). 100 cases of malignant tumor patients who received pelvic lymphadenectomy in hospital from January 2018 to January 2020 were analyzed. Patients were classified into control group (CTA image) and experimental group (RGA-based CTA image), each with 50 cases. The overall accuracy (OA) of the pelvic CT image segmentation parameters under RGA, the watershed segmentation algorithm (WA), and the swarm intelligence optimization algorithm (SIOA) was compared. Comparisons of segmentation parameters, denoising performance, and CT imaging of patients as well as diagnosis rate and total efficiency rate were carried out. The results showed that overall accuracy (OA) of RGA was considerably higher versus watershed segmentation algorithm (WA) and swarm intelligence optimization algorithm (SIOA). However, false positive rate (FPR) and false negative rate (FNR) of RGA were greatly lower than those of other algorithms. RGA greatly improved the accuracy of pelvic tumor detection. The peak signal-to-noise ratio (PSNR) of RGA was superior to that of WA and SIOA, but differences in edge preservation index (EPI) value were not significant. The diagnosis rate of the experimental group was 48/50 (96%), while the diagnosis rate by manual means was 38/50 (76%). For the diagnosis rate and total efficiency, results of the experimental group were evidently higher in contrast to the control group ( P < 0.05 ). In conclusion, under RGA, CTA image-guided pelvic lymphadenectomy had good segmentation accuracy and denoising performance, and it was superior in total efficiency and diagnosis rate, which was worthy of clinical promotion.
Highlights
Malignant pelvic tumors are mainly manifested as pelvic masses
Comparison of Pelvic CT Image Segmentation Parameters with Different Algorithms. e results of pelvic CT image segmentation parameters of different algorithms are shown in Figures 4 and 5. e region-growing algorithm (RGA) had overall accuracy (OA) of 0.905, false positive rate (FPR) of 0.0472, and false negative rate (FNR) of 0.0482. ose of watershed segmentation algorithm (WA) were 0.845, 0.0865, and 0.0845, respectively. ose of swarm intelligence optimization algorithm (SIOA) were 0.827, 0.1240, and 0.0742, respectively
It can be concluded that the OA of RGA was higher versus WA and SIOA, and both FPR and FNR were lower versus WA and SIOA
Summary
Malignant pelvic tumors are mainly manifested as pelvic masses. In addition to the history of pelvic masses, they are accompanied by lower abdomen enlargement, and CA125 is notably higher. For areas that suggest no echo, in most cases, part B is mixed echo, coating thickness is irregular, with double-sided, and carbohydrate antigen 125 (CA125) increases. Similar to that of the abdomen, the pelvis has two main compartments: the peritoneal cavity and the sub-peritoneal space, which are separated by the peritoneum, and each compartment is a continuous space [1, 2]. E sub-peritoneal cavity contains the entire abdominal and pelvic organs (and the respective mesenteric organs), extraperitoneal space ligaments, blood vessels, nerves, and lymphatic vessels Similar to that of the abdomen, the pelvis has two main compartments: the peritoneal cavity and the sub-peritoneal space, which are separated by the peritoneum, and each compartment is a continuous space [1, 2]. e sub-peritoneal cavity contains the entire abdominal and pelvic organs (and the respective mesenteric organs), extraperitoneal space ligaments, blood vessels, nerves, and lymphatic vessels
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