Rehabilitation Assessment of Lumbar Sports Injury based on Intelligent Analysis of MRI images

Abstract

Rehabilitation assessment of lumbar sports injury based on intelligent analysis of MRI images is studied in this paper. Only some important collected data are kept, which will not cause permanent loss of original image information. Using compressed sensing theory can greatly reduce the amount of sampled data, thus reducing the pressure for subsequent data transmission, processing and also storage. This technology innovatively changes the way of obtaining medical information, which can increase the speed to thousands of times, and then shorten the scanning time. The image segmentation method based on cluster analysis classifies and aggregates image pixels in the feature space and performs segmentation according to the similarity criterion; hence, these models are combined to construct the efficient model for the assessment of lumbar sports injury based on intelligent analysis of MRI images. Through the test on the robustness, the performance is validated.