Stila Ahawla
Scoliosis is a complex spinal deformity that affects millions of individuals worldwide. Accurate classification of scoliosis is crucial for determining appropriate treatment strategies. The Lenke classification system is widely used to categorize scoliosis based on curve type, magnitude, and flexibility. However, generating comprehensive and accurate Lenke classification reports can be time-consuming and subjective. To address these challenges, researchers have proposed a novel method that leverages dual attention to space and context for automated scoliosis Lenke classification report generation. This article aims to explore this innovative approach and its potential to enhance the efficiency and reliability of scoliosis classification.
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