Title:Investigation of Medical Image Technology Based on Big Data Neuroscience in
Exercise Rehabilitation
Volume: 20
Author(s): Shuhua Zhang and Jijin Sun*
Affiliation:
- College of Education, Qiongtai Normal University, Haikou 571127, Hainan, China
Keywords:
Exercise rehabilitation, Medical imaging technology, Big data neuroscience, Image fusion, CT images, MRI images.
Abstract:
Purpose:
The purpose of this article is to combine the functional information of CT images with the anatomical and soft tissue information of MRI through
image fusion technology, providing more detailed information for rehabilitation treatment and thus providing a scientific basis for clinical
applications and better training plans.
Methods:
In this paper, functional brain imaging technology combining CT (computed tomography) and MRI (magnetic resonance imaging) was used for
image fusion, and SURF (accelerated robust feature) feature points of images were extracted. In this study, 40 patients with mild and moderate
closed traumatic brain injury admitted to the rehabilitation department of a rehabilitation center from 2018 to 2022 were selected as the research
objects.
Results:
Compared with using only CT images and MRI images for brain injury diagnosis, the fusion image had a higher detection rate of abnormal brain
injury diagnosis, with a detection rate of 97.5%. When using fused images for the diagnosis of abnormal brain injury, the patient’s exercise
rehabilitation effect was better.
Conclusion:
CT and MRI image fusion technology had a high diagnostic accuracy for brain injury, which could timely guide doctors in determining exercise
rehabilitation plans and help improve the effectiveness of patient exercise rehabilitation.
