Self-Adaptive Particle Swarm Optimization of CT Images for Diagnosis of Severe Traumatic Brain Injury

Abstract

This paper aimed to explore the application values of computed tomography (CT) imaging in the treatment of patients with severe traumatic brain injury (STBI), to provide help in the treatment of STBI. In this study, 86 patients with STBI were selected as the research objects and examined by CT based on a self-adaptive particle swarm algorithm (APSO). Besides, patients were treated with hyperbaric oxygen, high-dose hormone shock, and naloxone hydrochloride. The results showed that there was a locally low-density brain contusion and laceration injury area, spot-like high-density hemorrhage, and subarachnoid hemorrhage in the images of CT examination. The ventricles of diffuse brain injury were compressed and reduced, and the white matter indicated that the ventricles and cisterns became smaller. Asymmetric hemorrhage and subarachnoid hemorrhage were scattered at the white matter junction. In short, subarachnoid hemorrhage, spot-like high-density hemorrhage at the injury site, and diminished ventricles were typical CT imaging manifestations of STBI. Naloxone hydrochloride method could effectively alleviate the matrix metalloproteinase-9 (MMP-9) (23.47 ± 3.45) and S100 calcium-binding protein B (S100B) (0.16 ± 0.06) of patients, which had reliable guiding significance for the later CT examination clinically.