A developmental stage-aware graph transformer framework for automated bone-age assessment

Abstract

By leveraging a skeletal graph structure based on anatomical relationships and incorporating a developmental stage-aware processing mechanism, the DSGTF framework provides an accurate and efficient automated solution for clinical bone-age assessment. The proposed approach exhibits strong stability and consistency across different age groups and sexes, making it a reliable tool for real-world medical applications. This model effectively simulates the clinical assessment process by dynamically adjusting attention to different skeletal regions based on developmental stages, mirroring the decision-making process of radiologists.

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