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Abstract Automated lumbar spine MRI analysis has made notable progress in recent years, yet existing methods still suffer from anatomical ambiguity, insufficient use of explicit structural priors, and limited modeling of inter-level degenerative dependency, which restrict their reliability for clinically meaningful burden assessment.
Abstract The incidence of spinal diseases is rising and affecting younger people, making early and accurate diagnosis based on medical imaging crucial for treatment. However, traditional manual segmentation and measurement suffer from issues such as judgment discrepancies, time-consuming processes, and subjective errors.
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