To realize the automatic symptom recognition and classification of MR images and improve the accuracy and efficiency of the diagnosis of lumbar intervertebral disc herniation (LDH), a method for lumbar intervertebral disc recognition and disease classification is proposed in this paper. The method mainly includes three steps: preprocessing, target segmentation, and symptom classification. Preprocessing is performed by noise reduction and interference removal methods for blurred images. The contour poles are used to determine the four points of the tail vertebra in order to reduce the wrong segmentation of the tail vertebra. A classification method based on five judgment indicators is proposed, which effectively improves the stability of disease diagnosis. The example verifies that the algorithm can accurately complete the target segmentation and the accuracy of symptom classification reaches the standard of professional doctors, which proves that the method has good robustness.
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