Abstract
To treat large intracranial aneurysms, pipeline embolization device (PED) stent with unsupervised learning algorithms was utilized. Unsupervised learning model algorithm was used to screen aneurysm health big data, find aneurysm blood flow and PED stent positioning characteristic parameters, and guide PED stent treatment of intracranial aneurysms. The research objects were 100 patients with intracranial large aneurysm admitted to X Hospital of X Province from June 2020 to June 2021, who were enrolled into two groups. One group used the prototype transfer generative adversarial network (PTGAN) model to measure mean blood flow and mean vascular pressure and guide the placement of PED stents (PTGAN group). The other group did not use the model to place PED (control group). The PTGAN model can learn feature information from horizontal and vertical directions, with smooth edges and prominent features, which can effectively extract the main morphological and texture features of aneurysms. Compared with the convolutional neural network (CNN) model, the accuracy of the PTGAN model increased by 8.449% (87.452%–79.003%), and the precision increased by 8.347% (91.23%–82.883%). The recall rate increased by 7.011% (87.231%–80.22%), and the F1 score increased by 8.09% (89.73%–81.64%). After the adoption of the PTGAN model, the average blood flow inside the aneurysm body was 0.22 (m/s). After the adoption of the CNN model, the average blood flow inside the aneurysm body was 0.21 (m/s), and the difference was 0.01 (m/s), which was considerable (p < 0.05). Through this research, it was found that the PTGAN model was better than the CNN model in terms of accuracy, precision, recall, and F1 score values. The PTGAN model was better than the CNN model in detecting the average blood flow rate and average blood pressure after treatment, and the blood flowed smoothly. Postoperative complications and postoperative relief were also better than those of the control group. In summary, based on the unsupervised learning algorithm, the PED stent had a good adoption effect in the treatment of intracranial aneurysms and was suitable for subsequent treatment.
Highlights
Cerebrovascular diseases are a kind of diseases threatening human life
Feature Map Visualization. e prototype transfer generative adversarial network (PTGAN) method used deep learning technology to automatically learn based on network loss, so the feature map output by the first convolutional layer of the image was visualized to show the performance of network feature extraction
Compared with the convolutional neural network (CNN) model, the accuracy of the PTGAN model increased by 8.449% (87.452%–79.003%), and the precision increased by 8.347% (91.23%–82.883%). e recall rate increased by 7.011% (87.231%–80.22%), and the F1 score increased by 8.09% (89.73%–81.64%). e results showed that the PTGAN model was better than the CNN model in terms of accuracy, precision, recall, and F1 score. e PTGAN model played an important role in classification and recognition performance
Summary
Cerebrovascular diseases are a kind of diseases threatening human life. With the continuous improvement of people’s living standard and diet style, the incidence of cerebrovascular diseases is increasing year by year. With the enlargement of the arterial tumor, the probability of aneurysm rupture will increase exponentially, so the active treatment of intracranial aneurysm is important [3]. Some aneurysms, such as large or giant aneurysms, Journal of Healthcare Engineering wide-necked aneurysms, fusiform aneurysms, and other complex aneurysms, have always been a difficult and challenging problem in clinical treatment [4]. The aneurysm neck is wide, the tumor is prone to rupture and hemorrhage, and the presence of important perforating vessels adjacent to or even on the tumor makes surgical treatment very difficult, resulting in high mortality, disability, and risk, which are the difficulties in the treatment of this aneurysm [5]. With the emergence of compliant balloon, spring coil, intracranial stent, etc., more and more neurosurgery centers have adopted interventional treatment for such lesions and achieved good clinical results [6]
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