Abstract

The objective of the present study was to explore the effects of early repair of traumatic craniocerebral injury on neural functions, as well as the optimal extraction of medical information from craniocerebral injury images. Therefore, a total of 60 patients with traumatic craniocerebral injury were submitted to decompressive craniectomy and then cranioplasty. Afterward, all the patients were divided into the early group and the routine group. The changes in indicators of both groups after the patients underwent decompressive craniectomy were compared and retrospectively analyzed. The National Institutes of Health stroke scale, Karnofsky performance status, and the Glasgow outcome scale scores in the 1st, 3rd, and 12th months after decompressive craniectomy of patients were observed. In terms of medical image information extraction, based on the active contour models of global region, the information was extracted from segmentation weak boundary images to quickly, completely, and clearly obtain the images of the cerebral region of patients with a traumatic craniocerebral injury. The results showed that the Glasgow outcome scale, Karnofsky performance status, and National Institutes of Health stroke scale scores of the early group were 3.23±0.67, 52.23±7.54, and 6.75±0.23, respectively. The Glasgow outcome scale, Karnofsky performance status and National Institutes of Health stroke scale scores of the routine group were 2.94±0.37, 51.42±4.68, and 6.32±0.24, respectively. The data of both groups were compared and the differences were not statistically significant. In the early group, the Glasgow outcome scale and National Institutes of Health stroke scores in the 6th month after trauma were 3.67±0.682 and 13.84±4.789, respectively, while in the routine group, these were 3.29±0.714 and 17.02±6.453, respectively and the differences were significant. It can be seen from the experimental results of extracting the target segmentation information that although the algorithm adds noise to the original image, it could accurately segment and extract the target region with little noise. It was not necessary to consider the selection of the initialization target, and the iteration could improve the segmentation efficiency of the algorithm. Also, it was found that given the condition of well-handled preoperative and preoperative indications, the early repair can promote the repair of neural functions of patients. Moreover, a contour model algorithm was proposed, which could effectively extract the medical information of the craniocerebral injury images, providing powerful theoretical guidance for the development of craniocerebral medical image information technology.