Abstract
This paper combines optimized CSMRI algorithm (CS) and magnetic resonance imaging (MRI) to shorten the scanning time of MRI image data and improve the imaging quality. At the same time, the paper applies functional magnetic resonance imaging (BOLD-fMRI) based on the principle of blood oxygen level dependence to explore the application value of the nerve function reconstruction therapy system for the rehabilitation of active and passive motor functions in patients with acute cerebral infarction. Methods. In this paper, 20 patients with acute cerebral infarction were included. The random drawing method was used to divide them into active group and passive group, each with 10 cases. Both groups were treated with conventional medication and acupuncture. The active group used the active mode of the nerve function reconstruction treatment system to guide the patients’ limb active exercise; all training in the passive group is provided by the nerve function reconstruction treatment system to passively exercise the patients’ limbs; both groups undergo BOLD-fMRI examination before treatment and after 2 weeks of treatment and observe the activated parts of the brain functional area and corresponding parts of the two groups before and after treatment. We observe the activation volume and, at the same time, the ADL score. Results. After treatment, the activation volume and ADL scores of brain functional areas in the two groups were significantly improved compared with those before treatment, and the difference was statistically significant ( P < 0.05 ). Conclusion. The combination of optimized CSMRI algorithm (CS) and magnetic resonance imaging (MRI) can be used to evaluate the early rehabilitation efficacy of patients with acute cerebral infarction and has certain guiding value for clinical treatment.
Highlights
With the aging of the population, stroke has become a serious public health problem in the world, with high disability, mortality, and recurrence rates, which seriously affect the quality of life and physical health of patients
Optimized CSMRI Algorithm e main content of the optimized CSMRI algorithm refers to the following: signals with a sparse representation in a certain transform domain can be collected in a way that is far Scientific Programming below the standard of the Nyquist sampling theorem, sampling can be done through random projections that are incoherent with the transform basis, and the appropriate optimization algorithm can be done to reconstruct the original signal with high probability and accuracy. e theoretical framework mainly includes three aspects: sparse representation, measurement matrix, and reconstruction algorithm
Twenty patients with acute cerebral infarction who were treated in our hospital from October 2017 to May 2019 were divided into 10 cases in the active and passive groups by random drawing and were given different rehabilitation treatments. e study had been approved by the Medical Ethics Committee of the Hospital, and the patients and their families had understood the situation of the study and signed the informed consent forms
Summary
With the aging of the population, stroke has become a serious public health problem in the world, with high disability, mortality, and recurrence rates, which seriously affect the quality of life and physical health of patients. Functional magnetic resonance imaging based on the principle of blood oxygen level dependence was used to carry out active and passive exercise rehabilitation before and after the study of patients with acute cerebral infarction. E theoretical framework mainly includes three aspects: sparse representation, measurement matrix, and reconstruction algorithm (see Figure 1 for details) The reconstruction algorithms of the optimized CSMRI algorithm are mainly divided into four categories: greedy algorithm, convex optimization algorithm, combination algorithm, and statistical optimization algorithm [2]
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